EP3815037A1 - System und verfahren zur erzeugung eines mehrparametrigen grafischen indikators aus einem bild eines histologischen schnittes - Google Patents

System und verfahren zur erzeugung eines mehrparametrigen grafischen indikators aus einem bild eines histologischen schnittes

Info

Publication number
EP3815037A1
EP3815037A1 EP19752216.2A EP19752216A EP3815037A1 EP 3815037 A1 EP3815037 A1 EP 3815037A1 EP 19752216 A EP19752216 A EP 19752216A EP 3815037 A1 EP3815037 A1 EP 3815037A1
Authority
EP
European Patent Office
Prior art keywords
interest
quantities
component
estimated
area
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP19752216.2A
Other languages
English (en)
French (fr)
Inventor
Yvon JULE
Forent TOMI
Jean-Claude Gilhodes
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Biocellvia
Original Assignee
Biocellvia
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Biocellvia filed Critical Biocellvia
Publication of EP3815037A1 publication Critical patent/EP3815037A1/de
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G06T11/20—Drawing from basic elements, e.g. lines or circles
    • G06T11/206—Drawing of charts or graphs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30061—Lung
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/40—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H70/00—ICT specially adapted for the handling or processing of medical references
    • G16H70/60—ICT specially adapted for the handling or processing of medical references relating to pathologies

Definitions

  • the invention relates to a system and method for producing a multi-parameter graphical indicator related to the reshaping of the epithelium of a tissue of a human or animal organ, from an image of a histological section and thus, deliver objective and reproducible aid to health personnel so that they can establish a diagnosis in connection with a possible human or animal pathology.
  • the invention further provides objective and reproducible aid so that an experimenter in the laboratory can estimate the curative relevance of a treatment given with regard to such a pathology.
  • Biological imaging is currently one of the major resources for exploring organs and various organic tissues. She is particularly active in the areas of medical diagnosis assistance and preclinical and clinical research.
  • a second technique consists in evaluating lung volumes by plethysmography. It provides a sensitive measure of trapped gases and pulmonary hyperinflation, which can be defined as an abnormal rise in lung volumes at the end of expiration. This measurement gives a function of the limitation of the air flow, the phenomenon of elastic retraction of the lungs and the compliance of the chest wall of a patient. A narrowing of the airways in fact leads to an increase in the expiration time necessary to evacuate all the air contained in the lungs. This may cause the airways to close, trapping the remaining gas.
  • the Residual Volume (RV) of gas remaining also consists of a measurement indicating a dysfunction of the small respiratory tracts.
  • Said volume can be directly correlated with the degree of morphological changes in the respiratory tract due to inflammation present in the small airways.
  • a ratio of said Residual Volume on total pulmonary capacity (TLC) which we can note RV / TLC, can be easily established by this method, in the same way as an airway resistance which increases during obstructive pulmonary diseases.
  • this indicator is not specific to the small respiratory tract, which limits its application in the diagnosis and surveillance of SAR-type diseases.
  • SPECT to an English acronym.
  • Such a three-dimensional imaging technique consists in using several gamma ray detectors which move around a patient in the lying position. A reconstruction of the images obtained then makes it possible to visualize a distribution of the radionuclides in three dimensions, thus offering an evaluation of the ventilation of different pulmonary regions.
  • the SPECT analysis technique can induce a major drawback and a health risk for a patient when looking for pathologies, having regard to the radiation applied to said patient.
  • Limitations on the intensity of said radiation and / or the acquisition time of experimental signals may impact the evaluation of the elimination of the radionuclides after deposition of the latter in the various pulmonary regions of interest, thus obstructing a relevant evaluation of the ventilation of said pulmonary regions of the patient.
  • the invention makes it possible to respond to all or part of the drawbacks previously raised and makes it possible to offer precious help to any experimenter wishing to estimate quantities of interest with a view to producing a graphical indicator, to facilitate the establishment of '' a diagnosis related to a human or animal pathology, or even to estimate the relevance of a treatment with regard to said pathology.
  • Some chronic lung diseases are characterized by remodeling of lung tissue (SAR) affecting the alveolar parenchyma, bronchi, and vessels.
  • SAR lung tissue
  • the invention allows a highly precise quantitative morphometric analysis of the components observed in a histological section, thus making it possible to characterize, for example, a reshaping of the respiratory tract, and thus makes it possible to deliver a multi-parameter graphical indicator linked to the morphology of tubular components of an organ, including the lungs, and more specifically the small airways.
  • the invention uses a digital representation of a histological section of said organ, describing a plurality of annular components resulting from the section of said tubular components to make a histological section. Said tubular components are manifested by annular components in a two-dimensional representation, after a histological section. The notion of tubular component will be described in more detail below in connection with FIG. 3.
  • the invention relates to a method for producing a multi-parameter graphical indicator relating to a reshaping of the human or animal bronchial epithelium from a digital representation, in a matrix form of a determined number of pixels, of a histological section of a lung comprising one or more components of annular shape each of which describes a wall surrounding a light, the method being implemented by a unit of processing of a histological analysis system, said system further comprising a man-machine output interface and a data memory.
  • said method comprises:
  • a step for estimating, from pixels of said digital representation of a histological section of a lung, quantities of interest relating to the respective morphologies of the components identified in said digital representation of the histological section, said quantities of interest belonging to a set of interest quantities comprising:
  • the step for estimating quantities of interests relating to the respective morphologies of the components identified in said digital representation of the histological section can comprise a step for writing into the data memory a data structure associated with each component, said structure of data including a field to record the value of each estimated quantity of interest.
  • the method may include a step for characterizing a type of component from the value of one of the estimated quantities of interest, the step of writing into the data memory a data structure associated with each estimated quantity of interest of a component can consist in registering in a field of said data structure a value characterizing a type of component determined.
  • the step to characterize a type of component of a process according to the invention may include an operation of comparing the value of said diameter of Feret estimated at a high diameter threshold and / or a low diameter threshold.
  • the step for characterizing a type of component of a method according to the invention may include an operation of comparing the value of said average thickness with a predetermined high thickness threshold and / or a predetermined low thickness threshold.
  • the step for characterizing a type of component of a process according to the invention may include an operation of comparing the value of said area with a predetermined high area threshold and / or a low area threshold.
  • the step to produce, by quantity of interest estimate, a graphical representation thereof relating to a quantity of standard interest and / or the step for causing the joint graphic rendering of the graphical representations of said quantities of interest relating to the quantities of standard interest cannot be implemented as for a specific type of characterized component.
  • a method according to the invention provides that the type of characterized component determined can be a bronchiole .
  • the step in order to provide an experimenter with visual aid making it possible to instantly compare estimated quantities of interest, reflecting a possible change in morphology of the components from which said estimated quantities of interest are derived in order to orient the diagnosis of '' a pathology, the step, to cause the joint graphical restitution of the graphical representations of said quantities of interest relating to the quantities of respective standard interest previously produced by the man-machine interface output of the system, can consist in displaying by the latter of a Kiviat diagram.
  • a Kiviat diagram can describe at least three graphical representations of quantities of interest relative to the quantities of respective standard interest on standardized axes.
  • the step for causing the joint graphic restitution of the graphical representations of said quantities of interest relating to the quantities of respective standard interest previously produced by the man-machine interface output of the system may consist in the display by the latter of a bar diagram describing the graphical representations of quantities of relative interest to the respective standard interest quantities by standard bars.
  • the normalization of an axis or a bar of the step to cause joint graphical rendering graphical representations of said quantities of interest relative to the quantities of respective standard interest previously produced by the human-machine interface output of the system may consist in expressing the value of an estimated quantity of interest as a percentage of the value of the amount of associated standard interest.
  • the normalization of an axis or of a step bar for cause the graphic rendering joint graphical representations of said quantities of interest relating to the respective standard interest quantities previously produced by the man-machine interface output of the system may consist in expressing the value of an estimated quantity of interest relative to the value of the quantity of standard interest associated in the form of three predetermined values respectively describing values of quantity of interest estimated to be substantially lower, close to or greater than the values of the quantities of standard interest associated.
  • the invention also relates to an electronic object of a histological analysis system, said electronic object comprising a processing unit and cooperating with an output human-machine interface and with a data memory, said memory of data comprising:
  • the invention also relates to a histological analysis system comprising an electronic object according to the second object of the invention and an output human-machine interface. able to restore to a user a multi-parameter graphical indicator according to a process in accordance with the first object of the invention and implemented by said electronic object.
  • the invention finally relates to a computer program product comprising one or more instructions interpretable or executable by an electronic object in accordance with the second object of the invention, the interpretation or the execution of said instructions by said unit of processing causes the implementation of a process in accordance with the first object of the invention.
  • FIG. 1 shows a first digital representation of a histological section of a lung, of a subject suffering from SAR, said subject in this case being a mouse;
  • FIG. 2 illustrates a second binary digital representation, resulting from that presented in FIG. 1, said second binary digital representation highlighting pixels of interest with regard to the other pixels;
  • FIG. 4A presents a first example of graphical representation in the form of a bar diagram, of a multiparametric graphical indicator produced by a method according to the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of quantities of respective standard interest on standardized axes, in a subject suffering from acute SAR;
  • FIG. 4B presents a second example of graphical representation in the form of a Kiviat diagram, of a multiparametric graphical indicator produced by a method in accordance with the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of quantities of respective standard interest on standardized axes, in a subject suffering from acute SAR;
  • FIG. 5 presents a first example of graphical representation in the form of a bar diagram, of a multiparametric graphical indicator produced by a method in accordance with the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of quantities of respective standard interest on standardized axes, in a subject suffering from acute SAR;
  • FIG. 6 presents a second example of graphical representation in the form of a Kiviat diagram, of a multi-parameter graphical indicator produced by a method according to the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of respective standard interest quantities on standardized axes, in a subject suffering from acute SAR;
  • FIG. 7A presents a first example of graphical representation in the form of a bar diagram, of a multiparametric graphical indicator produced by a method in accordance with the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of quantities of respective standard interest on standardized axes, in a subject suffering from acute SAR;
  • FIG. 7B presents a second example of graphical representation in the form of a Kiviat diagram, of a multiparametric graphical indicator produced by a method in accordance with the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of quantities of respective standard interest on standardized axes, in a subject suffering from acute SAR;
  • FIG. 8 presents a first example of graphical representation in the form of a bar diagram, of a multi-parameter graphical indicator produced by a method in accordance with the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of quantities of respective standard interest on standardized axes, in a subject suffering from acute SAR;
  • FIG. 9 presents a second example of graphical representation in the form of a Kiviat diagram, of a multiparametric graphical indicator produced by a method in accordance with the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of quantities of respective standard interest on standardized axes, in a subject suffering from acute SAR;
  • FIG. 10 shows a simplified flowchart illustrating a non-limiting example of a method for producing a multi-parameter graphical indicator relating to a tissue of a human or animal organ according to the invention.
  • FIG. 1 describes a first RDI digital representation of a histological section of a lung of a subject suffering, for example, from a remodeling of the small airways or SAR. Said subject is in this case a mouse.
  • a first RDI representation is generally the result of a process of digitizing a histological section.
  • a histological section digitized with an enlargement x20 delivers said first digital representation in a matrix form of approximately two hundred million pixels, that is to say according to the example of FIG.
  • RGB color coding (acronym for "Red Green Blue”), also known by the acronym RGB (acronym for "Red Green Blue”).
  • RGB color coding (acronym for "Red Green Blue”)
  • RGB ancronym for "Red Green Blue”
  • RGB coding indicates a value for each of these primary colors. Such a value is generally coded on a byte and therefore belongs to a range of integer values between zero and two hundred and fifty-five.
  • the RDI representation presents, in a distinguishable manner, at the center of said representation, the lobe L of a lung.
  • a member also comprises numerous substantially tubular components Ci, the internal walls of which respectively form openings. Following the cut made at the pulmonary lobe, only sections of said tubular components Ci are visible in two dimensions. The latter can be described, in particular in connection with FIG. 3, as annular structures, the ring of which is a section of the wall of the component Ci, encircling a hole associated with the light.
  • Such tubular components Ci mainly consist of vessels, bronchi, bronchioles or also alveoli which can form alveolar bags. The rest of the tissue P of said lobe is hereinafter called "parenchyma".
  • the lung injury results in changes in the morphology of some of the tubular components that make up the lung, in particular by a reshaping of the airways, more particularly of the bronchioles in the case of SAR.
  • the diameters of the bronchioles are generally comprised, within the taxon of vertebrates, between one hundred microns and one thousand microns. SAR therefore involves, in the early stages of a subject's airway involvement, flaking of the bronchial epithelium, more commonly known as the "bronchial wall", characterized on a digital representation of a histological section of a lung, by a ring representing a section of such a bronchial wall.
  • Such desquamation generally induces a reduction in the area of the bronchioles and of said bronchial wall, characterized on a digital representation of a histological section of a lung, by a reduction in the area of the ring and possibly of the 'area surrounded by said ring, that is to say the area of the section of a lumen of said tubular component.
  • a more severe attack induces a reshaping of such bronchioles and a modification of the metabolism of these, materializing by a chronic inflammation of the bronchial wall leading to changes in the morphology of said bronchioles.
  • FIG. 1 thus describes a first digital representation RDI, of a lobe L of a lung OG of a subject suffering from SAR.
  • Said first RDI digital representation is, according to the state of the art, difficult to use for an experimenter to be able to determine the presence of morphometric modifications induced by a possible reshaping of the small airways, characterizing a pathology such as SAR. Indeed, said morphometric modifications being of the order of a micron, it is very difficult for an experimenter to note them from a histological section.
  • the techniques described above are preferred for characterizing, in subjects, the involvement of small airways.
  • the invention plans to focus on morphometric properties of the components found in a histological section of a lung by the exploitation of a digital representation, obtained by scanning said histological section.
  • a single digital representation of a histological section of a subject presenting an attack of the small airways is represented, the differences with a digital representation of '' a histological section of a healthy subject being imperceptible by the human eye.
  • a method according to the invention may include a prior step consisting of a processing for binarizing said first digital representation RDI and producing a second digital representation MRI.
  • a second digital representation MRI can be produced by any type of known digital processing aimed at binarizing a digital representation in color (s), such as the digital representation RDI.
  • Such a digital representation or image is expressed in the form of a table comprising the same number of elements or pixels as the first digital RDI representation of a histological section from which it is derived, such as the first digital RDI representation previously mentioned in link with FIG. 1.
  • Said second digital representation MRI is said to be binary because each of its elements MRI (i, j), designated by two indexes i and j respectively determining the row and the column of said element or pixel in the table MRI, comprises an integer value chosen from two predetermined values signifying respectively that the pixel RDI (i, j), that is to say of the same column j and of the same row i in a first digital representation RDI, designates or not part of lobe L.
  • FIG. 2 illustrates an example of a second binary representation MRI, the second binary digital representation MRI in this case being derived from the first digital representation RDI described in connection with FIG. 1.
  • an MRI element (i, j) of the MRI table takes the value zero if the associated pixel RDI (i, j), that is to say designated by the line i and the column j in the first digital representation RDI, does not correspond to a pixel of the lobe L, that is to say that said described pixel is a light formed by the transverse section of a tubular component, or the outside of the lobe L of the lung. Otherwise, such an MRI element (i, j) takes the value two hundred fifty-five.
  • Such a second binary digital representation MRI can be displayed in black and white on a computer screen.
  • the invention cannot be limited to the use of said values zero and two hundred and fifty-five.
  • other predetermined values could have been chosen from said values zero and two hundred fifty-five to characterize the absence of interest or the interest of such a pixel.
  • a processing 10 to produce a binary MRI representation of an RDI digital representation can be implemented before the implementation of a method for producing a multiparametric indicator according to the invention, such as a method 100, a non-limiting example of which is particularly described in connection with FIG. 10.
  • a method 100 a non-limiting example of which is particularly described in connection with FIG. 10.
  • a component tubular of interest Ci translates in a digital representation RDI or MRI by an annular structure in two dimensions.
  • Said processing 10 aimed at binarizing a digital representation can, as a variant, constitute a first step of said method 100 mentioned above.
  • a nonlimiting example of a processing 10, aimed at binarizing such a first RDI digital representation may include a first step to produce a first intermediate digital representation in shades of gray, not illustrated by the figures for the purposes of simplification.
  • Said intermediate digital representation comprises the same number of elements or pixels as the first RDI digital representation.
  • Such a first step may consist in the implementation of any known technique for converting, for each pixel of the RDI representation, the triplet of values representing the levels of the primary colors into an integer value representing a luminosity or a luminous intensity associated with a representation pixel thus produced.
  • Said first step may also consist in applying, to the digital representation thus produced, a median or bilateral filter to remove certain aberrations.
  • a second step of such processing 10 aimed at binarizing a digital representation according to the invention may consist in implementing an automatic thresholding of the pixels of the (first) intermediate digital representation, so as to discriminate the pixels describing all or part of d 'a lumen formed by the cross section of a tubular component or the outside of the Lobe L of the lung.
  • the pixels associated with a light or outside the lobe take the value zero, thus appearing in black in FIG. 2.
  • the other pixels take the value two hundred and fifty-five and appear in white. They are associated with parenchymal tissue or certain tubular components such as vessels, alveoli, alveolar bags, bronchi or even bronchioles.
  • This second step thus produces a second binary digital representation MRI.
  • Such processing 10 aimed at binarizing a digital representation can, in addition, produce a third binary digital representation, which we will call “Lobe mask”, of the same dimensions as the second binary digital representation MRI, each element of which has a first value specifying that an associated pixel within an RDI or MRI digital representation belongs to or is outside the lobe.
  • Lobe mask of the same dimensions as the second binary digital representation MRI, each element of which has a first value specifying that an associated pixel within an RDI or MRI digital representation belongs to or is outside the lobe.
  • a pixel of the second binary digital representation MRI will only be taken into account if and only if, the associated pixel in said lobe mask, it is that is, with the same row and column indexes, has a value characterizing a pixel belonging to the lobe L examined.
  • Such a third digital representation can be produced in addition to the second stage of a processing 10 aimed at binarizing a digital representation, by the search for the largest contour by the implementation, for example, of a "Flood Fill" algorithm according to English terminology Saxon or also known by the French name "algorithm by filling by diffusion".
  • FIG. 10 describes a nonlimiting exemplary embodiment of a method 100 for producing a multi-parameter graphical indicator I relating to a reshaping of the epithelium of a human or animal organ from a digital representation of a histological section of said organ according to the invention, whether such a representation is in the form of a digital RDI or binary MRI color representation.
  • Such a method 100 and / or such a preliminary processing 10, aiming at binarizing a digital representation RDI and producing a digital representation MRI, can be arranged to be transcribed into a computer program, the program instructions of which can be installed in a program memory of an electronic object, in the form for example of a computer having sufficient computing power and / or suitable for the analysis of digital representations or of images of consequent sizes, taking account of the precision necessary for the analysis of a pulmonary lobe L.
  • processing unit means one or more microcontrollers or microprocessors cooperating with a program memory hosting the computer program according to the invention.
  • processing unit can also be arranged to cooperate with a data memory for hosting, that is to say recording, the digital representations produced by the implementation of a method 100 for producing a multi-parameter graphical indicator I relating to a remodeling of the bronchial epithelium according to the invention and / or any other data necessary for the implementation of the latter.
  • Such a processing unit can also be arranged to cooperate with a man-machine interface or output device, such as a computer screen, a printer or any other interface to deliver the content of said multi-parameter graphical indicator I to a human, perceptibly through one of its senses.
  • a man-machine interface or output device such as a computer screen, a printer or any other interface to deliver the content of said multi-parameter graphical indicator I to a human, perceptibly through one of its senses.
  • such a method 100 for producing a multi-parameter graphical indicator I can comprise a sequence 110 possibly iterative, of steps aiming to estimate, from a first digital representation RDI and / or MRI of a section histological of a tissue of a human or animal organ, one or more quantities of QI interest relating to the respective morphologies of the components Ci present in said histological section.
  • Said iterative sequence of a method for producing a multi-parameter graphical indicator I comprises a step 111 for estimating one or more quantities of QI interests.
  • the implementation of step 111 may advantageously include a succession of sub-steps, not shown in FIG. 10, consisting in "searching", from a RDI and / or MRI digital representation of a histological section, a first light described by cutting a substantially annular component Ci.
  • step 111 consists in determining, from RDI and / or MRI digital representations, topologies of components Ci present in said digital representation RDI and / or MRI. It is then possible to determine the contour of an area associated with a light from a component Ci previously identified, this being akin to a binary digital representation MRI with a set of contiguous pixels describing for example a number of equal values to zero. Step 111 then consists in delimiting the interior contour of said lumen, that is to say, consequently, that of the internal wall of said identified component.
  • Step 111 now consists in determining, from such a first polyline, the outline of the outer wall of the component Ci previously identified.
  • a step 111 for estimating one or more quantities of interest of such a method 100 for producing a multi-parameter graphical indicator I can implement a technique, such as that known under the name "morphological expansion of the internal contour" described in the work of Jean Serra, Image Analysis and Mathematical Morphology, 1982, or any other equivalent technique.
  • step 111 of a method 100 for producing a multi-parameter graphical indicator I now consists in estimating an amount of interest QI relating to said morphology of said component Ci, the light of which has previously been identified.
  • a component of interest Ci thus has, in two dimensions, a substantially annular shape as described in an example in connection with FIG. 3, advantageously but not limitingly for a CTi type of component Ci, in this case a bronchiole.
  • Said bronchiole, and more generally a type of component Ci comprises an exterior contour CWOCi, an interior contour CWICi enclosing a light CLi, and a wall CWi, the corresponding areas of which are designated by a round-headed arrow.
  • different quantities of IQ interest can be estimated in step 111 of a process according to the invention. As described in connection with FIG. 3, such amounts of interest can consist of:
  • the term "Feret diameter” means the greatest distance between two tangents to the second polyline describing the apparent external contour CWOCi of the wall CWi of said component Ci, said tangents being parallel between them and perpendicular to a vector of given direction.
  • the average distance CWWi which will be called average thickness CWWi for simplification, from the wall CWi of a component Ci previously identified.
  • average thickness CWWi means the ratio between the sum of the estimated distances separating the external contour CWOCi from the internal contour CWICi of said component Ci previously identified and the number of estimated distances.
  • the CWi wall of certain Ci components found in the lungs may undergo total scaling or partial.
  • the term “the area ICAi” means the surface of a section describing the light CLi of a component Ci, said surface being delimited by the first polyline of said component Ci;
  • OCAi area means the surface describing the light CLi of a component Ci, said surface being delimited by the first polyline of said component Ci, as well as the surface described by the wall of said component Ci, said surface describing the wall being delimited by the first polyline and the second polyline of said component Ci;
  • step 111 of a method 100 for producing a multi-parameter graphical indicator I in accordance with the invention makes it possible, from the first and second polylines previously produced, respectively associated to the internal contour CWICi and to the external contour CWOCi, to estimate one or more quantities of interest QI, such as the diameter of Feret DFi of a component Ci.
  • a nonlimiting example of such a step 111 for estimating such a diameter consists in summing the pixels of known dimensions, in order to deduce therefrom a corresponding distance characterizing said diameter.
  • the distance relative to each diameter can thus be estimated, and the largest distance corresponding to the diameter of Féret DFi can thus be recorded during the implementation of a step 113 of a method 100 to produce a multiparametric graphical indicator I conforms to the invention, in a data structure associated with the component Ci.
  • Step 111 of a method 100 for producing a multi-parameter graphical indicator I in accordance with the invention may, as a variant or in addition, consist in estimating an average distance CWWi reflecting an average thickness of the wall CWi of a component Ci beforehand identified.
  • An example of such a step 111 for estimating such an average distance CWWi can consist in estimating, for each pixel of a first and / or a second polyline respectively describing the inner contour CWICi and the apparent outer contour CWOCi of the wall CWi of said component Ci, the smallest distance separating said pixel from said first and / or second polylines.
  • a plurality of distance estimates describing the thickness of the wall CWi of the corresponding component Ci can thus be estimated, so that, by means of said estimates, the implementation of such a step 111 makes it possible to estimate an average distance CWWi translating the average thickness of the wall CWi of said component Ci.
  • Said average distance can also be entered during the implementation of step 113 of a method 100 to produce a multi-parameter graphical indicator I conforming to l invention, in a data structure associated with the component Ci.
  • Step 111 of a method 100 for producing a multi-parameter graphical indicator I in accordance with the invention may, as a variant or in addition, consist in estimating an area ICAi translating the surface of the light CLi of a component Ci previously identified.
  • An example of such a step 111 for estimating such an area ICAi may consist in summing the pixels of known dimensions, describing the surface delimited by said first polyline. The implementation of such a step 111 thus makes it possible to estimate the area ICAi, corresponding to the sum of the areas of the pixels describing the light CLi, of the component Ci previously identified.
  • Said area ICAi may also be registered during the implementation of a step 113 of a method 100 for producing a multi-parameter graphical indicator I according to the invention, in a data structure associated with the component Ci.
  • Step 111 of a method 100 for producing a multiparametric graphic indicator I in accordance with the invention can also consist in estimating an area OCAi reflecting the surface of a component Ci previously identified.
  • An example of such a step 111 for estimating such an area OCAi may consist in summing the pixels of known dimensions describing the area delimited by said second polyline.
  • the implementation of such a step 111 makes it possible to estimate the area OCAi, corresponding to the sum of the areas of the pixels describing the entire area of the component Ci previously identified.
  • Said area OCAi may also be registered during the implementation of a step 113 of a method 100 for producing a multi-parameter graphical indicator I according to the invention, in a data structure associated with the component Ci.
  • step 111 of a method 100 for producing a multi-parameter graphical indicator I according to the invention may consist in estimating an area CAi reflecting the surface of the wall CWi of a component Ci previously identified.
  • An example of such a step 111 for estimating such an area CAi may consist in subtracting the area ICAi described by the interior contour CWICi of a component Ci, from the area OCAi described by the exterior contour CWOCi of the same component Ci, and previously estimated.
  • Said area CAi may also be entered during the implementation of a step 113 of a method 100 for producing a multi-parameter graphical indicator I according to the invention, in a data structure associated with the component Ci.
  • sequence 110 of a method 100 for producing a multi-parameter graphical indicator I can also include a step 113 for writing into the data memory, a data structure associated with each component Ci identified and whose morphology was characterized during a step 111 of said method 100.
  • Said data structure can advantageously include a field for recording the value of each quantity of interest estimated QI corresponding corresponding to said component Ci, such as , for example, the Feret diameter DFi of said component Ci, an average thickness CWWi of the wall CWi of said component Ci, the area ICAi describing the light CLi of said component Ci, the area OCAi describing the total surface of said component Ci and l CAi describing the total surface of the wall CWi of said component Ci.
  • a field for recording the value of each quantity of interest estimated QI corresponding corresponding to said component Ci such as , for example, the Feret diameter DFi of said component Ci, an average thickness CWWi of the wall CWi of said component Ci, the area ICAi describing the light CLi of said component Ci, the area OCAi describing the total surface of said component Ci and l CAi describing the total surface of the wall CWi of said component Ci.
  • said sequence can be implemented iteratively for one or more contours of one or more CLi lumens characteristic and respective of one or more components Ci identified .
  • a sequence may also include a test step 114, of so that when there is no other contour surrounding a light CLi characteristic of a component Ci yet unidentified, situation illustrated by the link 114n in FIG.
  • step 113 the estimation of one or more amounts of interest per iteration, as represented by the link 114y between step 113 and step 111, ends and the data relating to said amounts of interest are ready to be used by step 120 of the method 100 described by way of nonlimiting example in FIG. 10.
  • a method 100 for producing a multi-parameter graphical indicator I in accordance with the invention may include a step 112 , prior to step 113 to write in the data memory a data structure associated with a component Ci, to characterize a type CTi of component Ci, from the value of one of the quantities of interest QI estimated during step 111, present in a histological section of an OG lung, such as by way of nonlimiting examples, types of components discriminating alveoli and / or alveolar bags, bronchioles, bronchi and vessels.
  • step 112 to characterize a CTi type of component Ci can consist of comparing, in a sub-step 1121, the value of the Feret diameter DFi of a component Ci, estimated during the implementation of step 111, at a high diameter threshold DFh and / or a low diameter threshold DFb, said thresholds DFh and DFb being advantageously and previously configurable.
  • said sub-step 1121 could consist in assigning a predetermined value, for example the value "1" to a dedicated field in the data structure associated with said component Ci, if the diameter of Féret The latter's DFi is greater than a low diameter threshold DFb of one hundred micrometers and less than a high diameter threshold DFh of one thousand micrometers.
  • a predetermined value for example the value "1"
  • DFb low diameter threshold
  • DFh high diameter threshold
  • the use of the Feret diameter proves to be particularly advantageous, since such a use thus facilitates the classification of the different types CTi of components Ci and allows an experimenter to take into consideration only one or more types of components of interest among the different CTi types of components Ci identified, to subsequently produce a multiparametric graphical indicator I providing valuable assistance in establishing a diagnosis of a pathology affecting the respiratory tract.
  • a step 112 to characterize a type CTi of a component Ci of a process of a process 100 for producing a multi-parameter graphical indicator I according to the invention can consist in comparing, in a sub-step 1122, the value of the average thickness CWWi of a component Ci, estimated during the implementation of step 111, at a high average thickness threshold CWWh and / or a low average thickness threshold CWWb, said thresholds CWWh and CWWb being advantageously and previously configurable.
  • said sub-step 1122 could consist in assigning said predetermined value "1" in a dedicated field in the data structure associated with said component Ci, if the average thickness CWWi of the latter is greater than a high diameter threshold CWWh of ten micrometers.
  • the CTi types of Ci components observed in a histological section of an OG lung generally have an average thickness CWWi greater than 10 micrometers.
  • the use of the average thickness CWWi of the wall CWi can facilitate the classification of the different types CTi of components Ci and allow an experimenter to take into consideration only the type or types CTi of components Ci of interest, for producing later , a multi-parameter graphical indicator I providing valuable assistance in establishing a diagnosis of a pathology affecting the respiratory tract.
  • a step 112 for characterizing a CTi type of component Ci of a method 100 for producing a multi-parameter graphical indicator I according to the invention can consist in comparing, in a sub-step 1123, the value of the area ICAi described by the internal contour CWICi of a component Ci, estimated during the implementation of step 111, at a high area threshold ICAh and / or a low area threshold ICAb, said ICAh and ICAb thresholds being advantageously and previously configurable.
  • said sub-step 1123 may consist in assigning the predetermined value "1" in a field dedicated to the type of component in the data structure associated with said component Ci, if the area ICAi of the latter is lower than a low area threshold ICAb of twelve thousand square micrometers and higher than a high area threshold ICAh of fifteen thousand square micrometers.
  • the CTi types of components Ci observed in a histological section of an OG lung, more particularly the bronchioles generally have an ICAi area substantially equal to thirteen thousand square micrometers.
  • the use of the area ICAi thus facilitates the classification of the different types CTi of components Ci and / or the differentiation of the different stages of attack such as the acute and chronic stages, within the framework of a pathology such as SAR, and allows an experimenter to take into consideration only the CTi type (s) of components Ci considered of interest, to subsequently produce a multi-parameter graphical indicator I providing precious assistance in establishing a diagnosis of a pathology affecting the respiratory tracts.
  • step 112 to characterize a CTi type of component Ci of a method 100 for producing a multi-parameter graphical indicator I according to the invention can be arranged to jointly exploit different quantities of interest .
  • a method 100 for producing a multi-parameter graphical indicator I can be arranged to jointly exploit different quantities of interest .
  • said step 112 can consist first of all in comparing, in a sub-step 1124, the value of the Feret diameter DFi of a component Ci estimated, during the implementation of step 111 at a high diameter threshold DFh and / or a low diameter threshold DFb, said thresholds DFh and DFb being advantageously and previously configurable. If said value of the Feret diameter DFi of a component Ci is between said thresholds DFb and DFh, said sub-step 1124 can then consist in comparing the value of the average thickness CWWi of said component Ci, estimated during the setting in work of step 111, at a high average thickness threshold CWWh of ten micrometers, advantageously at a high average thickness threshold CWWh of five micrometers.
  • a method 100 for producing a multi-parameter graphical indicator I provides that said sub-step 1124 is firstly arranged to compare the value of the Feret diameter DFi of a component Ci to a low diameter threshold DFb of one hundred micrometers and a high diameter threshold DFh of one thousand micrometers.
  • said step 1124 may consist, in a second step, in comparing the value CWWi of said component Ci, estimated during the implementation of step 111, with a high average thickness threshold CWWh of five micrometers. Thus, if such an average thickness CWWi is greater than said thickness threshold CWWh, then said sub-step 1124 may consist in assigning said predetermined value "1" in a dedicated field in the data structure associated with said component Ci.
  • said sub-step 1124 may consist in assigning said predetermined value "2" in a dedicated field in the data structure associated with said component Ci.
  • a value predetermined "1" may by way of advantageous but non-limiting example, characterize a component Ci of the bronchiole type.
  • the implementation of such a sub-step 1124, jointly exploiting a plurality of quantities of interest, can thus facilitate the classification of the different types CTi of components Ci whose morphologies are close, such as, for example, the components Ci bronchiole type and alveolus and / or alveolar sac type.
  • step 113 for writing into the data memory a data structure associated with each component Ci identified can also consist in entering in a dedicated field of said data structure a predetermined value to characterize, from one or more quantities of interest, a particular CTi type of a component Ci, such as for example the type bronchiole.
  • a method 100 for producing a multi-parameter graphical indicator I in accordance with the invention may include a step 115 for filtering the data previously estimated and written into the data memory, making it possible to take account of that data relating to one or more types CTx determined from among all the values of types CTi of components Ci identified, in order to finally and subsequently produce a multi-parameter graphical indicator I relating to said data.
  • a step 115 may consist in reading, in the data structure associated with a component Ci, the value present in the field characterizing the type CTi of said component Ci.
  • said step 115 can advantageously be set so that only the data, more particularly the quantity or quantities of interest previously estimated relating to the components Ci of CTx type “bronchiole”, associated with such a type of component Ci comprising, in the field characterizing the type CTi of said component Ci, a predetermined value CTx for example equal to "1", are used to subsequently produce a multi-parameter graphical indicator I, with a view to providing assistance in the diagnosis of a pathology such as, by way of nonlimiting example, SAR.
  • a method 100 for producing a multi-parameter graphical indicator I in accordance with the invention may include a step 116 for estimating an average for each set of quantities of interest QI by type CTi of component Ci.
  • L step 116 can thus produce, for a given type CTi of component Ci, possibly previously filtered during the implementation of step 115, one or more average quantities of IQ interest, from the quantities of interest QI estimated respectively for all the components Ci.
  • set of quantity of interest QI means all the values previously estimated, for example relative: - the Feret Diameter DFi of the external contour CWOCi of the wall CWi for a CTi type of component Ci given;
  • step 116 of a method 100 for producing a multi-parameter graphic indicator I in accordance with the invention may consist in estimating , for a set of Ci components of the bronchiole type:
  • the average Feret diameter DFm corresponding to the ratio between the sum of the Feret DFi diameters of the Ci components of the bronchiole type and the number of Ci components of which a Feret DFi diameter has been previously estimated
  • the average thickness CWWm corresponding to the ratio between the sum of the average thicknesses CWWi of the components Ci of bronchiole type and the number of said components Ci of which said thickness CWWi has been previously estimated
  • the average area ICAm of the lights CLi corresponding to the ratio between the sum of the areas ICAi estimated of the components Ci of the bronchiole type and the number of components Ci for which the area ICAi has been previously estimated
  • the average area OCAm corresponding to the ratio between the sum of the areas OCAi of the components Ci of the bronchiole type and the number of components whose area OCAi has been previously estimated
  • the average area CAm corresponding to the ratio between the sum of the areas CAi of the components Ci of the bronchiole type and the number of components whose area CAi has been previously estimated.
  • a method 100 for producing a multi-parameter graphical indicator I in accordance with the invention may include a step 120 consisting in producing one or more graphical representations, intended to transcribe one or more quantities of QI interest, such that, for example of nonlimiting examples, the quantities of interest DFi, CWWi, ICAi, OCAi, CAi previously estimated, in a graphical form.
  • Said method 100 can then include a step 130 to cause the joint graphical restitution of said graphical representations previously produced in step 120, and deliver a multiparametric graphical indicator I.
  • a step 120 of a method 100 for producing a multi-parameter graphical indicator I according to the invention can consist in producing a graphical representation, for a type CTi of component Ci given and / or previously selected by means of an input human-machine interface, an amount of QI interest relative to a quantity of standard interest.
  • the term “quantity of standard interest” is understood to mean a quantity of reference interest, possibly configurable, associated with each quantity of estimated IQ interest. In accordance with the examples previously described, such a quantity of standard interest may consist, nonexhaustively, in:
  • the average Feret diameter DFe corresponding to the ratio between the sum of the Feret DFi diameters of the Ci components of the bronchiole type and the number of Ci components of which a Feret DFi diameter was previously estimated in a healthy subject;
  • the average thickness CWWe corresponding to the ratio between the sum of the average thicknesses CWWi of the components Ci of bronchiole type and the number of said components Ci of which said thickness CWWi has been previously estimated in a healthy subject;
  • the mean area ICAe of the lights CLi corresponding to the ratio between the sum of the areas ICAi estimated of the components Ci of the bronchiole type and the number of components Ci whose area ICAi was previously estimated in a healthy subject;
  • the average area OCAe corresponding to the ratio between the sum of the areas OCAi of the components Ci of the bronchiole type and the number of components whose area OCAi has been previously estimated in a healthy subject; the mean area CAe corresponding to the ratio between the sum of the areas CAi of the components Ci of the bronchiole type and the number of components whose area CAi has been previously estimated in a healthy subject.
  • a healthy subject is defined as a subject presenting no pathology affecting the airways, such as, by way of nonlimiting example, SAR.
  • the graphical representations of the quantities of interest QI of a type CTi of component Ci produced during step 120 to produce a graphical representation and / or step 130 to produce a multiparametric graphical indicator I can be expressed in relative or normalized value, thus allowing said quantities of interest to be expressed on a common scale and consequently jointly comparable, such quantities of interest being preferably but not limitatively expressed as a percentage of quantities of interest corresponding standard.
  • such a step 120 may consist in producing a graphical representation in the form of a bar of a bar diagram representing, for example, one of the quantities of interest IQ previously estimated, the height or length of which, depending on whether the bar is respectively vertical or horizontal, describes the relative value of said quantity of interest estimated with regard to said quantity of standard interest.
  • Said graphical representation can also encode one or more data determined to characterize, during the display of said graphic representation via a man-machine output interface during step 130, a particular texture, pattern or outline, or even any other data making it possible to impact the graphic rendering.
  • a step 120 of a method 100 according to the invention can consist in producing a graphical representation in the form of a point on an axis of a Kiviat diagram representing, for example, one of the quantities of QI interest previously estimated, the position of which on said axis describes the relative value of said quantity of interest estimated with regard to said quantity of standard interest .
  • the average quantities of interest DFm, CAm, CWWm, ICAm estimated for a type CTi of component Ci, of a digital representation d 'a histological section of an organ of a subject can be compared jointly and respectively to the quantities of standard interest DFe, CAe, CWWe, ICAe corresponding to a healthy subject.
  • a method 100 for producing a multi-parameter graphical indicator I the production of the graphical representations in step 120 of said method 100 will be described for a type of component Ci of interest in the form of a bronchiole, with a view to producing a multi-parameter graphical indicator I.
  • a multi-parameter graphical indicator I is notably described in connection with FIGS.
  • step 130 after implementation of step 130 to cause the joint graphical reproduction of the graphical representations of the quantities of interest, such as, for example, the average quantities of interest DFm, CWWm, ICAm, CAm, relative to the quantities d interest DFe, CWWe, ICAe, CAe in a healthy subject.
  • said quantities of interest DFm, CWWm, ICAm and CAm can be respectively expressed as a percentage or normalized with respect to a quantity of standard interest, the numerical value of the percentage being juxtaposed with the digital representation concerned.
  • a grid symbolized for example by axes “50% CTL” and “100% CTL”, qualified as “standard bars”, as presented in connection with FIG.
  • FIG. 4A illustrates a first nonlimiting example of graphical representation in the form of a bar diagram of a multiparametric graphical indicator produced by a method according to the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of respective standard interest quantities on axes normalized, in a subject with acute SAR.
  • a step 120 may consist in expressing a first quantity of interest DFm, in the form of a bar, relative to a quantity of standard interest DFe, symbolized by the "100% CTL" axis of the grid.
  • the graphical representation DFm encodes a numerical value of seventy-seven percent, meaning that the average Feret diameter DFm in the subject examined is twenty-three percent less than the average Feret diameter in a healthy subject .
  • step 120 may advantageously consist in expressing a second quantity of interest CWWm, in the form of a bar, with respect to a quantity of CWWe standard interest, symbolized by the "100% CTL" axis of the grid.
  • step 120 may advantageously consist in expressing a third quantity of interest ICAm, in the form of a bar, relative to to a quantity of standard interest ICAe, symbolized by the "100% CTL" axis of the grid.
  • step 120 may advantageously consist in expressing a fourth quantity of interest CAm, in the form of a bar, in relation to a quantity of standard interest CAe, symbolized by the “100% CTL” axis of the grid.
  • the graphic representation CAm encodes a numerical value of seventy percent, meaning that the average area CAm of the walls in the subject examined is twenty-one percent less compared to the average area of the walls in a healthy subject. It will thus be possible, during the implementation of step 130, to cause the joint graphic reproduction of said graphic representations thus produced via a man-machine interface output from a system implementing a method 100 according to the invention , in the form, for example, of bar diagrams, in order to provide an experimenter with a multi-parameter graphical indicator I, presenting the different bars side by side.
  • FIG. 4A Such a first example of joint graphical restitution, in the form of a bar diagram, is presented in FIG. 4A for a subject respectively suffering from a so-called acute SAR.
  • said FIG. 4A jointly expresses the respective graphic representations of the first, second, third and fourth quantities of interest DFm, CWWm, ICAm and CAm in the form of a graphical representation of the bar diagram type, and express the respective values of said interest amounts DFm, CWWm, ICAm and CAm relative to those of the same amounts of interest DFe, CWWe, ICAe and CAe in a healthy subject.
  • a multi-parameter graphical indicator I provides relevant information concerning the general morphology of all the components of the bronchiole type present in a histological section of a lung of an affected subject. acute SAR.
  • Such an attack generally induces a more or less heterogeneous desquamation of the bronchial epithelium, that is to say a decrease in the average thickness CWWi of the wall CWi of the bronchioles.
  • This desquamation of the bronchial wall leads, consequently, to a decrease in the total area CAi of the bronchiole, possibly in the area ICAi of the lumen CLi and in the diameter of Féret DFi.
  • steps 120 and / or 130 of a method for producing such an indicator multiparametric graph I can, by way of nonlimiting examples, consist in expressing and then displaying averaged quantities of interest, in the form of a graphical representation of the Kiviat diagram type, also known by the name "radar", relative or relative to these same amounts of standard interest, said quantities of standard interest being indicated as corresponding to 100% with respect to a graduated axis.
  • Such an axis can be graduated, by way of nonlimiting example, from zero percent of the value of the corresponding standard quantity in a healthy subject.
  • each quantity of QI interest can be normalized with regard to the corresponding standard interest quantity and can be displayed after graphical restitution during step 130 in a continuous scale.
  • FIG. 4B illustrates a second nonlimiting example of graphical representation in the form of a Kiviat diagram of a multiparametric graphical indicator I produced by a method 100 according to the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of quantities of respective standard interest on standardized axes, in a subject suffering from acute SAR.
  • such a step 120 may consist in expressing a first quantity of interest DFm, in the form of a position on a graduated axis, with respect to a quantity of standard interest DFe, symbolized by position 100 on the graduated axis.
  • step 120 may advantageously consist in expressing a second quantity of interest CWWm, under the form of a position on a graduated axis, relative to a quantity of standard interest CWWe, symbolized by position 100 on the graduated axis.
  • step 120 can advantageously consist in expressing a third quantity of interest ICAm, in the form of a position on an axis. graduated, relative to a quantity of standard interest ICAe, symbolized by position 100 on the graduated axis.
  • step 120 may advantageously consist in expressing a fourth quantity of interest CAm, in the form of a position on a graduated axis, relative to a quantity of standard interest CAe, symbolized by position 100 on the graduated axis.
  • step 130 to cause the joint graphic rendering of said graphic representations thus produced via a man-machine interface output from a system implementing a method 100 according to the invention, such as, for example of nonlimiting example, in the form, for example of a Kiviat diagram, in order to provide an experimenter with a multi-parameter graphical indicator I.
  • a joint graphical restitution can further illustrate the materialization of an area defined by the different respective positions of the standardized quantities of interest on the standardized axes.
  • FIG. 4B Such a first example of joint graphic restitution, in the form of a diagram of Kiviat, is presented in FIG. 4B for a subject suffering from a so-called acute SAR.
  • 4B jointly expresses the graphic representations of the first, second, third and fourth quantities of interest DFm, CWWm, ICAm and CAm in the form of a graphical representation of the Kiviat diagram type.
  • the area, describing the joint positions of the quantities of interest DFm, CWWm, ICAm and CAm, delimited by a dotted outline, can thus easily indicate the pathological state of the morphology of the components Ci of interest represented on each axis of the diagram with regard to the area, indicated by the solid outline, describing a typical morphology of such components in a healthy subject.
  • the components Ci of interest of the bronchiole type present in a digital representation of a histological section of a lung, have quantities of interest which have decreased by compared to the same amounts of standard interest.
  • FIG. 5 illustrates a third nonlimiting example of graphical representation in the form of a bar diagram of a multiparametric graphical indicator produced by a method according to the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of respective standard interest quantities on axes normalized, in a subject with acute SAR.
  • FIG. 5 jointly expresses respective graphic representations of the first, second, third and fourth quantities of interest DFm, CWWm, ICAm and CAm in the form of a graphical representation of diagram type. bars.
  • FIG. 5 presents respective graphic representations of the first, second, third and fourth quantities of interest DFm, CWWm, ICAm and Cam in the form of signed relative deviations, such deviations consisting of calculated positive or negative numerical values from the mathematical formula
  • Em consists of the value of the estimated average deviation, consists of the value of the quantity of average interest estimated in a subject examined, e consists of the value of the quantity of standard interest in a healthy subject.
  • such a step 120 may consist in expressing signed relative differences between first, second, third and fourth quantities of interest DFm, CWWm, ICAm and CAm, respectively in the form of bars , compared to a zero vertical or horizontal horizon described by an axis "100% CTL".
  • Such deviations can thus represent a relative or normalized decrease or increase in said first, second, third and fourth quantities of interest DFm, CWWm, ICAm and CAm, relative to respective reference quantities of interest.
  • a vertical horizon a decrease in such an amount of interest is displayed on the left while an increase in such an amount of interest is displayed on the right.
  • step 130 it will thus be possible, during the implementation of step 130, to cause the joint graphic reproduction of said graphic representations thus produced via a man-machine interface output from a system implementing a method 100 according to the invention , in the form, for example, of bar diagrams, in order to provide an experimenter with a multi-parameter graphical indicator I, presenting the different bars side by side.
  • FIG. 6 illustrates a fourth nonlimiting example of graphical representation in the form of a Kiviat diagram of a multiparametric graphical indicator I produced by a method 100 according to the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of quantities of respective standard interest on standardized axes, in a subject suffering from acute SAR.
  • Figures 4A, 4B and 5 jointly expresses respective graphical representations of the first, second, third and fourth quantities of interest DFm, CWWm, ICAm and CAm in the form of a graphical representation of type Kiviat diagram.
  • FIG. 4A, 4B and 5 jointly expresses respective graphical representations of the first, second, third and fourth quantities of interest DFm, CWWm, ICAm and CAm in the form of a graphical representation of type Kiviat diagram.
  • FIG. 1 illustrates a fourth nonlimiting example of graphical representation in the form of a Kiviat diagram of a multiparametric graphical indicator I produced by
  • Em ⁇ 0e Em 0.1
  • such a step 120 can consist in expressing determined absolute differences between first, second, third and fourth average interest quantities DFm, CWWm, ICAm and CAm and first, second, third and fourth quantities of respective and corresponding standard interest, respectively in the form of positions on graduated axes.
  • Such deviations can thus represent an absolute and normalized decrease or increase, in this case according to three predetermined increasing values "0.1", "0.5” and "1", of the said first, second, third and fourth quantities of interest DFm, CWWm, ICAm and CAm, in relation to the respective standard quantities of interest.
  • the invention cannot be limited to values Advantageously, the deviations Em.
  • the deviations or said quantities of interest DFm, CWWm, ICAm and CAm can be respectively expressed by an index characterizing a decrease, an equivalence or an increase compared to a quantity of standard interest, in l 'species such an equivalence to a quantity of standard interest is represented on each axis of the diagram, by the corresponding graduation "0,5".
  • the invention provides a configurable or predetermined tolerance threshold, for example plus or minus ten percent around the standard value to thereby determine such equivalence between the estimated quantity of interest and the corresponding standard quantity.
  • the invention provides that below such a threshold, said quantity of interest is considered to be less, value "0.1", or greater value "1", than said quantity of standard interest .
  • such a fourth example of graphical representation in the form of a Kiviat diagram, can advantageously be arranged to display an increase or a decrease for each quantity of estimated IQ interest. relative to a quantity of standard interest if and only if said quantity of QI interest is greater or less than a configurable threshold.
  • Such a joint graphic reproduction can also illustrate the materialization of an area defined by the respective respective positions of the normalized quantities of interest on the normalized axes.
  • FIG. 4B Such a first example of joint graphical restitution, in the form of a Kiviat diagram, is presented in FIG. 4B for a subject suffering from a so-called acute SAR.
  • the area, describing the joint positions of the quantities of interest DFm, CWWm, ICAm and CAm, delimited by a dotted outline can thus easily indicate the pathological state of the morphology of the components Ci of interest represented on each axis of the diagram with regard to the area, indicated by the solid outline, describing a typical morphology of such components in a healthy subject.
  • the area describing the pathological state is reduced or zero compared to the air describing the typical morphology.
  • FIGS. 7A, 7B, 8 and 9 respectively illustrate first, second, third and fourth nonlimiting examples of graphical representations in the form of bar diagrams and of diagrams.
  • Kiviat of a multi-parameter graphical indicator I produced by a method 100 according to the invention, said indicator describing a plurality of estimated quantities of interest relating to a plurality of respective standard quantities of interest on standardized axes, in a subject has chronic SAR.
  • Such a multi-parameter graphical indicator I is thus particularly suitable for describing the morphology of the bronchioles. Indeed, it is known that a pathology, such as SAR, can induce long-term chronic inflammation of the bronchioles, causing a remodeling of the latter.
  • FIGS. 7A, 7B, 8 and 9 jointly express respective graphic representations of the first, second, third and fourth quantities of interest DFm, CWWm, ICAm and CAm under the form of graphical representations such as bar charts and Kiviat charts.
  • a multi-parameter graphical indicator I is applied to a second histological section of a lung of a subject this time suffering from chronic SAR.
  • a pathology is easily diagnosed by an experimenter at the sight of one or more multi-parameter graphical indicators I.
  • a multiparametric graphical indicator I as presented in FIG. 7A, provides relevant information concerning the general morphology of all the components of the bronchiole type present in a histological section of a lung of a subject suffering from chronic SAR.
  • Such an attack generally induces a more or less significant inflammation of the bronchioles.
  • the experimenter can easily note that the same amounts of interests DFm, ICAm and CAm are manifestly higher than in a healthy subject.
  • the use of such a Kiviat diagram also makes it possible to directly oppose quantities of interest IQ supposed to be correlated with one another.
  • the production of a multiparametric graphical indicator I in the form of a Kiviat diagram makes it possible to visually highlight an increase in the internal surface of the lumens CLi and more generally in the size of the bronchioles respectively described, in connection with FIG. 7B , by the area ICAm and the diameter of Féret DFm.
  • Figures 8 and 9 all the more highlight average interest quantities CWWm and CAm substantially identical to the quantities of standard interest, while the average quantities of interest DFm and ICAm are clearly increasing, such quantities of average interest being characteristic of a subject suffering from chronic SAR.
  • a method 100 for producing a multiparametric graphic indicator I according to the invention may include a step 132 to cause the rendering or graphic output of such a multiparametric graphic indicator I according to the invention by any suitable human-machine interface, such as, for example, without limitation a computer screen, cooperating with the electronic object implementing said method 100.
  • a restitution or output can be written or audible , respectively via a printer-type output device or a sound output device via a speaker.
  • a method 100 for producing a multiparametric graphical indicator I may include one or more steps 131, 133, 134, to cause graphical restitution of digital representations of the RDI, MRI type and of the estimated IQ interest amounts in the form of cards. Such cards can be restored graphically by means of an output device identical or distinct from that delivering the previously developed multi-parameter graphical indicator, quantity of interest by quantity of interest in step 120.
  • the user of an electronic object adapted to implement a process in accordance with the invention such as method 100 has a plurality of objective, reproducible and instantaneous information helping to diagnose a pathology such as SAR.
  • All of the steps 131 to 134 thus constitute a processing 130, intended to restore to the user a multiparametric graphic indicator I, one or more quantities of estimated QI interest, or even one or more cards, in this case, one or more several digital representations among the RDI, MRI digital representations mentioned above.
  • the invention provides that the estimated quantities of interest DFi, CAi, CWWi, ICAi, or more generally a quantity of interest QI, for each type CTi of component Ci, of a digital representation of a histological section of an organ of a subject examined, can no longer be compared to the corresponding standard interest quantities in a healthy subject, but to the average interest quantities DFm, CAm, CWWm, ICAm estimated in this same subject.
  • one or more stages of graphic rendering 133 or 134 of a method 100 according to the invention may also consist in assigning, to the pixels associated with a component Ci of interest, a color and / or a determined value expressing a significant increase or decrease with respect to the average morphology of the other components.
  • the invention has in particular been described in connection with the analysis of a pulmonary lobe of a mouse. However, it cannot be limited to this single example of implementation and / or application. Other modifications can be envisaged without departing from the scope of the present invention in order to adapt, as a variant or in addition, the method for producing a multi-parameter graphical indicator in humans or another animal, or even to an organ having anatomical similarities with lung.
  • the invention cannot be limited to graphic representations in the form of bar diagrams and / or Kiviat diagrams previously described, the quantities of interest of which are expressed in particular as a function of the quantity of standard interest.
  • other representations suitable for producing a multi-parameter graphical indicator I could have been used.

Landscapes

  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • General Health & Medical Sciences (AREA)
  • Physics & Mathematics (AREA)
  • Primary Health Care (AREA)
  • Epidemiology (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Biomedical Technology (AREA)
  • Pathology (AREA)
  • Databases & Information Systems (AREA)
  • Radiology & Medical Imaging (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Geometry (AREA)
  • Quality & Reliability (AREA)
  • Image Processing (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)
EP19752216.2A 2018-06-29 2019-06-28 System und verfahren zur erzeugung eines mehrparametrigen grafischen indikators aus einem bild eines histologischen schnittes Withdrawn EP3815037A1 (de)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR1855953A FR3083358A1 (fr) 2018-06-29 2018-06-29 Systeme et procede pour produire un indicateur graphique multiparametrique a partir d'une image d'une coupe histologique
PCT/FR2019/051614 WO2020002859A1 (fr) 2018-06-29 2019-06-28 Système et procédé pour produire un indicateur graphique multiparamétrique à partir d'une image d'une coupe histologique

Publications (1)

Publication Number Publication Date
EP3815037A1 true EP3815037A1 (de) 2021-05-05

Family

ID=65685421

Family Applications (1)

Application Number Title Priority Date Filing Date
EP19752216.2A Withdrawn EP3815037A1 (de) 2018-06-29 2019-06-28 System und verfahren zur erzeugung eines mehrparametrigen grafischen indikators aus einem bild eines histologischen schnittes

Country Status (4)

Country Link
US (1) US20210264596A1 (de)
EP (1) EP3815037A1 (de)
FR (1) FR3083358A1 (de)
WO (1) WO2020002859A1 (de)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3656308A1 (de) * 2018-11-20 2020-05-27 Koninklijke Philips N.V. Vorrichtung zur alveolenbasierten visualisierung in der dunkelfeld- oder phasenkontraströntgenbildgebung

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2012107050A1 (en) * 2011-02-08 2012-08-16 Region Nordjylland, Aalborg Sygehus A system for determining flow properties of a blood vessel
US10176408B2 (en) * 2015-08-14 2019-01-08 Elucid Bioimaging Inc. Systems and methods for analyzing pathologies utilizing quantitative imaging

Also Published As

Publication number Publication date
US20210264596A1 (en) 2021-08-26
WO2020002859A1 (fr) 2020-01-02
FR3083358A1 (fr) 2020-01-03

Similar Documents

Publication Publication Date Title
EP3755197B1 (de) Verfahren zur automatischen bestimmung der anzeigequalität der bilder, die bei einer kapselendoskopie übertragen werden
EP1932118B2 (de) Verfahren und vorrichtung zur bestimmung von hautmängeln und verfahren zur schätzung des antialterungseffekts von kosmetikprodukten
FR2862788A1 (fr) Procede et systeme d'analyse de changements temporels d'image
CN112075922B (zh) 2型糖尿病眼底图像指标的测量及与糖尿病肾病相关性的分析方法
EP2652702B1 (de) Verfahren zur detektion und quantifizierung von unschärfe auf einem digitalbild
EP2494520A1 (de) Verfahren und vorrichtung zur analyse hyperspektraler bilder
JP6461084B2 (ja) アルツハイマー病又は軽度認知機能障害の検出支援システム
KR20190087681A (ko) 자궁경부암에 대한 피검체의 발병 여부를 판정하는 방법
FR3062498B1 (fr) Systeme et procede pour l'evaluation de risques vasculaires
US11776115B2 (en) System and method for estimating a quantity of interest based on an image of a histological section
WO2020002859A1 (fr) Système et procédé pour produire un indicateur graphique multiparamétrique à partir d'une image d'une coupe histologique
EP3320462B1 (de) Verfahren zur unterstützung einer medizinischen diagnose
CN115965617A (zh) 一种基于集成学习的消化道内镜检查辅助系统
WO2020002860A1 (fr) Systeme et procede pour produire un indicateur graphique multiparametrique a partir d'une image d'une coupe histologique
FR2997536A1 (fr) Procede et systeme d'estimation d'un indice de severite differentiel d'une pathologie exprimant une alteration cutanee
Amba Learning methods for digital imaging.
US20240153288A1 (en) Systems and methods for quantitative polarization imaging
FR3050046B1 (fr) Procede et dispositif electronique d'aide a la determination, dans une image d'un echantillon, d'au moins un element d'interet parmi des elements biologiques, programme d'ordinateur associe
Rai et al. AI-Driven Smartphone Screening for Early Detection of Oral Potentially Malignant Disorders
Dokter Segmentation and classification of skin lesions using neural networks
Razaghi et al. Correction of Retinal Nerve Fiber Layer Thickness Measurement on Spectral-Domain Optical Coherence Tomographic Images Using U-net Architecture
WO2006042864A1 (fr) Traitement d'image identifiant des fibroses dans un tissu organique
Qiang et al. Vessel segmentation and quantification in ultra-wide-field OCTA images
Ferris Analysis of digitized cervical images to detect cervical neoplasia
CN115294011A (zh) 基于双模态光学扫描的视盘新生血管自动检测方法及系统

Legal Events

Date Code Title Description
STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: UNKNOWN

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE

PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE

17P Request for examination filed

Effective date: 20201209

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

DAV Request for validation of the european patent (deleted)
DAX Request for extension of the european patent (deleted)
STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE APPLICATION IS DEEMED TO BE WITHDRAWN

18D Application deemed to be withdrawn

Effective date: 20230103