WO2005031319A1 - Verfahren zur automatischen bestimmung auf einem träger gesammelter mikroorganismen - Google Patents
Verfahren zur automatischen bestimmung auf einem träger gesammelter mikroorganismen Download PDFInfo
- Publication number
- WO2005031319A1 WO2005031319A1 PCT/DE2004/002229 DE2004002229W WO2005031319A1 WO 2005031319 A1 WO2005031319 A1 WO 2005031319A1 DE 2004002229 W DE2004002229 W DE 2004002229W WO 2005031319 A1 WO2005031319 A1 WO 2005031319A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- image
- objects
- particles
- carrier surface
- color image
- Prior art date
Links
- 238000000034 method Methods 0.000 title claims abstract description 33
- 244000005700 microbiome Species 0.000 title claims abstract description 10
- 239000002245 particle Substances 0.000 claims abstract description 44
- 241000894006 Bacteria Species 0.000 claims abstract description 16
- 230000002538 fungal effect Effects 0.000 claims abstract description 13
- 238000010191 image analysis Methods 0.000 claims description 4
- 238000007781 pre-processing Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 abstract description 6
- 238000012544 monitoring process Methods 0.000 abstract description 3
- 241000894007 species Species 0.000 abstract description 3
- 239000000126 substance Substances 0.000 abstract 1
- 238000011161 development Methods 0.000 description 8
- 238000004040 coloring Methods 0.000 description 4
- 239000013598 vector Substances 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000011524 similarity measure Methods 0.000 description 2
- 239000013589 supplement Substances 0.000 description 2
- 239000000853 adhesive Substances 0.000 description 1
- 230000001070 adhesive effect Effects 0.000 description 1
- 244000052616 bacterial pathogen Species 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000001093 holography Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000004060 metabolic process Effects 0.000 description 1
- 230000002906 microbiologic effect Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 235000015097 nutrients Nutrition 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000000047 product Substances 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/10—Investigating individual particles
- G01N15/14—Optical investigation techniques, e.g. flow cytometry
- G01N15/1429—Signal processing
- G01N15/1433—Signal processing using image recognition
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/10—Investigating individual particles
- G01N15/14—Optical investigation techniques, e.g. flow cytometry
- G01N15/1468—Optical investigation techniques, e.g. flow cytometry with spatial resolution of the texture or inner structure of the particle
- G01N2015/1472—Optical investigation techniques, e.g. flow cytometry with spatial resolution of the texture or inner structure of the particle with colour
Definitions
- the invention relates to methods for the automatic determination of microorganisms collected on a carrier as airborne or water-borne particles in the form of fungal spores and bacteria.
- this carrier is advantageously located in a channel or at the end of a channel for supply air or water.
- the carrier is a filter or a body with a layer of an adhesive. After collection, the particles are incubated on nutrient media in microbiological laboratories. After several days, the colonies obtained can be evaluated. The colonies, which can all be traced back to only one collected germ, are roughly manually examined for color, shape and structure. A more precise determination of the types of germs is only possible after their separation, as well as growth and metabolism tests. This usually takes several weeks. These colonies are also determined manually.
- the object of the invention specified in claim 1 is to automatically determine microorganisms collected on a carrier in the form of fungal spores and bacteria as airborne or water-borne particles.
- the methods for the automatic determination of microorganisms collected on a carrier as airborne or water-borne particles in the form of fungal spores and bacteria are distinguished in particular by the fact that certain fungal spores and bacteria are automatically recognized and displayed and / or stored as a respective species.
- the method is therefore advantageously suitable for monitoring the atmosphere in and outside of buildings, the carrier being arranged in the supply air or the atmosphere.
- the method is also suitable for the monitoring of flowing or standing water, whereby the carrier is moved in the water or placed in the flowing water.
- the particles are advantageously automatically recognized in the method according to the invention.
- the particular advantage lies in the very quick determination of the presence of fungal spores and / or bacteria and the determination of the type of certain fungal spores or bacteria according to the content of the classifier. For this purpose, the carrier surface with the collected particles including the particles is recorded and the image of the
- Carrier surface digitized.
- This color image, a grayscale image converted from it and / or a silhouette image transformed therefrom is used to identify objects in the image.
- the individual objects are advantageously determined using a model-based comparison method.
- a case-based classification of the objects takes place via at least one feature determination.
- the specific objects are advantageously displayed and / or stored as a type.
- the result is a documentation of the results, which are available at any time as the current result and subsequently as a story.
- Another important advantage of the method according to the invention is that, in the presence of undefined and thus unclassified objects, they are displayed and / or stored as a color image and / or gray-scale image and / or silhouette image become. This enables you to manually determine or discard these objects.
- these manually determined objects are inserted as a new case with a certain class in the classifier.
- the classifier is continuously expanded so that the results of the procedures are refined.
- This provides a method for the automatic determination of microorganisms collected on a carrier as airborne or water-borne particles in the form of fungal spores and bacteria, which is constantly expandable. This is based on the open-ended case-based classifier.
- the different forms of spores or bacteria in their lives can also be included in their automatic determination. During their lifespan, they change their appearance and size according to the prevailing environmental conditions. There are thus different variations of spores or bacteria of one type, which can be determined automatically by using the method.
- the particles also accumulate in different positions on the carrier surface, so that different geometries of one type are recorded.
- the method is advantageously also distinguished by the fact that, depending on their position, these different geometries are included in the determination of the spores or bacteria.
- the number of specific objects is advantageously displayed and / or stored in this way. Threshold values can also be introduced in this way, for example an alarm not only being given when a certain number of specific particles is present but also when it is exceeded.
- the number is also advantageous of the undetermined objects are counted, so that when these particles are determined manually, their number is immediately displayed and / or stored. Repeated implementation with the extended classifier is avoided. Reactions to dangerous situations can be made more quickly.
- the image of the carrier surface with the air-borne particles is freed from faults and standardized in an image preprocessing after digitization according to the development of claim 4.
- the normalization advantageously compensates for colors and differences in the images.
- advantageous features for the determination of the objects are the shape, the texture or the structuring of the objects in the color image and / or in the gray value image.
- optically distinguishable features inside the objects are also included in the determination.
- the image of the carrier surface with the collected particles is recorded at least once two-dimensionally, spatially and / or three-dimensionally as a color image after the further development of patent claim 7.
- the depth of field depends on the set object width, the focal length and the aperture diameter. The basis is that when the camera lens is set to a certain image width, only object points in a certain object width are imaged as points on the recording plane. The images of object points with a smaller object width are created behind the image plane, those of points with a larger object width in front of the image plane.
- a spatial recording is the use of holography.
- the hologram can advantageously also be recorded using different imaging scales with a camera, for example as a digital camera. Another advantage is that the hologram can be reproduced with a plane wave with a larger or smaller wavelength, so that the images are also larger or smaller.
- the carrier surface with the collected particles is recorded as a color image and advantageously digitized at the same time.
- the image is taken using a device with an image enlargement, for example a microscope with a digital camera, so that a digitized image of the carrier surface with the particles is immediately available for further processing.
- this image is converted into a gray-scale image and in a second embodiment into a gray-scale image and subsequently into a silhouette image via at least one transformation step.
- a gray-scale image is created with the resulting full-area labeled objects of one gray-scale value and a background with a different gray-scale value.
- the objects are determined in the gray value image and / or in the silhouette image using a model-based comparison method.
- the model in the model-based comparison process consists of a set of points that describe the contour of the object and the associated direction vector. So far, models such as circles of different sizes, ellipses of different sizes and orientations and rectangles with rounded corners of different sizes and orientations have been designed.
- the transformed model is compared with the image at any point and a similarity measure is formed between the model and the pixels.
- the normalized point product of the direction vector of the transformed model and the vectors determined from the image is used to form a comparison measure.
- the normalized similarity measure has the property that it returns a value less than one as a result for the comparison.
- a result of one results if the model and object of the image match.
- the result also corresponds to the proportion of the model that is visible in the image.
- the model can also be rotated to improve the result, so that the result is greater than the previously determined result and equal to less than one.
- the detection of the objects in the grayscale image and / or silhouette image means that the contours of determined objects can be marked in the color image and / or in the grayscale image.
- the shape, the texture and the structure of objects determined as features in the color image and / or grayscale image are determined via this marking. From this, sizes of determined can advantageously also continue Objects. Such sizes include areas, dimensions in different directions and the circumference, so that further comparison possibilities are given.
- the characteristics form the basis for a subsequent case-based classification of the identified objects.
- the objects classified and determined thereby are displayed and / or saved as type, name and / or code.
- Detected and unclassified objects are also displayed and / or saved as a color image and / or grayscale image and / or silhouette image. This means that these objects can either be subsequently discarded or inserted as a new case with a specific class in the classifier.
- the stored knowledge in the classifier is expanded and refined, and on the other hand, the unclassified objects are documented, so that later processing can also take place.
- the objects are additionally counted. This can be done with the classified and certain objects as well as with the unclassified objects.
- the display and / or storage is supplemented by the respective number.
- the images are freed from interference and standardized in an image preprocessing after the recording and digitization.
- overlapping particles on the carrier surface are also included in the method for the automatic determination of particles collected on a carrier.
- overlapping particles of the color image or grayscale image are separated, hidden as objects from the color image and saved as a partial image.
- the overlapping objects of this partial image are separated from one another and are again stored as a partial image. Determinable features of the objects are determined in accordance with the exemplary embodiment and a comparison with objects in the classifier is carried out from these ascertained features. Missing areas can are supplemented in such a way that there is also a determination of these objects.
- the original and isolated object, the specific object determined by the supplement and the degree of agreement and thus the size of the supplement are advantageously displayed for manual determination and / or stored for documentation.
- the carrier surface can be colored to improve the determination of the particles.
- the coloring can take place both before and after an exposure.
Landscapes
- Chemical & Material Sciences (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Dispersion Chemistry (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Signal Processing (AREA)
- Engineering & Computer Science (AREA)
- Analytical Chemistry (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Image Analysis (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
Abstract
Description
Claims
Priority Applications (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP04789938A EP1671103A1 (de) | 2003-10-02 | 2004-10-01 | Verfahren zur automatischen bestimmung auf einem träger gesa mmelter mikroorganismen |
US10/574,176 US7711495B2 (en) | 2003-10-02 | 2004-10-01 | Methods for automatically identifying microorganisms collected on a carrier |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE10347123.5 | 2003-10-02 | ||
DE10347123A DE10347123B4 (de) | 2003-10-02 | 2003-10-02 | Verfahren zur automatischen Bestimmung auf einem Träger gesammelter luftgetragener Partikel insbesondere Pilzsporen |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2005031319A1 true WO2005031319A1 (de) | 2005-04-07 |
Family
ID=34384368
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/DE2004/002229 WO2005031319A1 (de) | 2003-10-02 | 2004-10-01 | Verfahren zur automatischen bestimmung auf einem träger gesammelter mikroorganismen |
Country Status (4)
Country | Link |
---|---|
US (1) | US7711495B2 (de) |
EP (1) | EP1671103A1 (de) |
DE (1) | DE10347123B4 (de) |
WO (1) | WO2005031319A1 (de) |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2006106235A1 (fr) * | 2005-04-08 | 2006-10-12 | Marc Alligier | Procede et dispositif de detection automatique de micro-organismes en temps reel et a intervalle de temps regulier dans un aerosol |
CN105259095A (zh) * | 2015-10-14 | 2016-01-20 | 南昌西尔戴尔医疗科技有限公司 | 宫颈癌细胞病理学排阴法智能筛查系统 |
WO2021186114A1 (fr) * | 2020-03-20 | 2021-09-23 | Prodose | Procede et dispositif de detection et de suivi de la presence, du developpement et de la propagation d'agents infectieux, notamment des bacteries et des virus |
Families Citing this family (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP5721233B2 (ja) * | 2009-12-28 | 2015-05-20 | サイバーアイ・エンタテインメント株式会社 | 画像認識システム |
EP2541492A1 (de) * | 2010-02-24 | 2013-01-02 | Fujitsu Frontech Limited | Authentifizierungsvorrichtung, authentifizierungsprogramm und authentifizierungsverfahren |
DE102011111155A1 (de) | 2011-08-19 | 2013-02-21 | Petra Perner | Verfahren zur fallbasierten Bestimmung von Gegenständen von in digitalisierter Form vorliegenden Bildern |
US10458990B1 (en) | 2015-03-06 | 2019-10-29 | Scanit Technologies, Inc. | Spore state discrimination |
US9933351B2 (en) | 2015-03-06 | 2018-04-03 | Scanit Technologies, Inc. | Personal airborne particle monitor with quantum dots |
US10684209B1 (en) | 2015-03-06 | 2020-06-16 | Scanit Technologies, Inc. | Particle collection media cartridge with tensioning mechanism |
WO2016201113A1 (en) * | 2015-06-09 | 2016-12-15 | Scanit Technologies, Inc. | Personal airborne particle monitor with quantum dots |
CN107688597B (zh) * | 2017-06-16 | 2021-12-21 | 湖北民族大学 | 一种大型真菌识别方法 |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4160601A (en) * | 1978-02-24 | 1979-07-10 | Nasa | Biocontamination and particulate detection system |
GB2254414A (en) * | 1991-03-21 | 1992-10-07 | Univ London | Volume measurement of microbial organisms. |
US5162990A (en) * | 1990-06-15 | 1992-11-10 | The United States Of America As Represented By The United States Navy | System and method for quantifying macrophage phagocytosis by computer image analysis |
EP0713087A1 (de) * | 1994-11-17 | 1996-05-22 | Chemunex | Vorrichtung und Verfahren zum schnellen und hochempfindlichen Erkennen und Zählen von Mikroorganismen mittels Fluoreszenz |
Family Cites Families (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
DE4244708C2 (de) * | 1992-04-09 | 1996-05-02 | Werner Maier | Verfahren und Vorrichtung zum Erstellen einer Artenliste für eine flüssige Probe |
DE19826835B4 (de) * | 1998-06-16 | 2006-02-02 | Perner, Petra, Dr.-Ing. | Anordnung und Verfahren zur automatischen Bestimmung luftgetragener Mikroorganismen, biotischer und/oder abiotischer Partikel |
WO2002068932A2 (en) * | 2001-02-23 | 2002-09-06 | Genicon Sciences Corporation | Methods for providing extended dynamic range in analyte assays |
-
2003
- 2003-10-02 DE DE10347123A patent/DE10347123B4/de not_active Expired - Fee Related
-
2004
- 2004-10-01 WO PCT/DE2004/002229 patent/WO2005031319A1/de active Application Filing
- 2004-10-01 EP EP04789938A patent/EP1671103A1/de not_active Withdrawn
- 2004-10-01 US US10/574,176 patent/US7711495B2/en not_active Expired - Fee Related
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4160601A (en) * | 1978-02-24 | 1979-07-10 | Nasa | Biocontamination and particulate detection system |
US5162990A (en) * | 1990-06-15 | 1992-11-10 | The United States Of America As Represented By The United States Navy | System and method for quantifying macrophage phagocytosis by computer image analysis |
GB2254414A (en) * | 1991-03-21 | 1992-10-07 | Univ London | Volume measurement of microbial organisms. |
EP0713087A1 (de) * | 1994-11-17 | 1996-05-22 | Chemunex | Vorrichtung und Verfahren zum schnellen und hochempfindlichen Erkennen und Zählen von Mikroorganismen mittels Fluoreszenz |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2006106235A1 (fr) * | 2005-04-08 | 2006-10-12 | Marc Alligier | Procede et dispositif de detection automatique de micro-organismes en temps reel et a intervalle de temps regulier dans un aerosol |
FR2884315A1 (fr) * | 2005-04-08 | 2006-10-13 | Marc Antoine Robert Alligier | Detecteur de presence de micro-organismes dans l'air |
CN105259095A (zh) * | 2015-10-14 | 2016-01-20 | 南昌西尔戴尔医疗科技有限公司 | 宫颈癌细胞病理学排阴法智能筛查系统 |
WO2021186114A1 (fr) * | 2020-03-20 | 2021-09-23 | Prodose | Procede et dispositif de detection et de suivi de la presence, du developpement et de la propagation d'agents infectieux, notamment des bacteries et des virus |
FR3108438A1 (fr) * | 2020-03-20 | 2021-09-24 | Prodose | Procede et dispositif de detection et de suivi de la presence, du developpement et de la propagation d’agents infectieux, notamment des bacteries et des virus |
Also Published As
Publication number | Publication date |
---|---|
US20070207451A1 (en) | 2007-09-06 |
DE10347123B4 (de) | 2005-07-28 |
DE10347123A1 (de) | 2005-05-04 |
US7711495B2 (en) | 2010-05-04 |
EP1671103A1 (de) | 2006-06-21 |
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