NZ764955B2 - Three-dimensional medical image analysis method and system for identification of vertebral fractures - Google Patents

Three-dimensional medical image analysis method and system for identification of vertebral fractures Download PDF

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Publication number
NZ764955B2
NZ764955B2 NZ764955A NZ76495518A NZ764955B2 NZ 764955 B2 NZ764955 B2 NZ 764955B2 NZ 764955 A NZ764955 A NZ 764955A NZ 76495518 A NZ76495518 A NZ 76495518A NZ 764955 B2 NZ764955 B2 NZ 764955B2
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NZ
New Zealand
Prior art keywords
voxels
sets
size
image
fracture
Prior art date
Application number
NZ764955A
Other versions
NZ764955A (en
Inventor
Joeri Nicolaes
Original Assignee
UCB Biopharma SRL
Filing date
Publication date
Priority claimed from GBGB1720059.3A external-priority patent/GB201720059D0/en
Application filed by UCB Biopharma SRL filed Critical UCB Biopharma SRL
Publication of NZ764955A publication Critical patent/NZ764955A/en
Publication of NZ764955B2 publication Critical patent/NZ764955B2/en

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B2576/00—Medical imaging apparatus involving image processing or analysis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/02—Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03—Computed tomography [CT]
    • A61B6/032—Transmission computed tomography [CT]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/50—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
    • A61B6/505—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for diagnosis of bone
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00—Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52—Devices using data or image processing specially adapted for radiation diagnosis
    • A61B6/5211—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data
    • A61B6/5217—Devices using data or image processing specially adapted for radiation diagnosis involving processing of medical diagnostic data extracting a diagnostic or physiological parameter from medical diagnostic data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G06F18/2415—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on parametric or probabilistic models, e.g. based on likelihood ratio or false acceptance rate versus a false rejection rate
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/08—Volume rendering
    • 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
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10081—Computed x-ray tomography [CT]
    • 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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • 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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]
    • 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
    • G06T2207/30008—Bone
    • G06T2207/30012—Spine; Backbone
    • 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
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/11—Region-based segmentation
    • 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
    • G16H50/20—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

Abstract

The present invention provides a machine-based learning method to estimate a probability of bone fractures in a 3D image, more specifically vertebral fractures. The method and system utilizing such method utilize a data-driven computational model to learn 3D image features for classifying vertebra fractures, that producing two or more sets of 3D voxels, wherein each of the sets corresponds to the entire said 3D image, and wherein each of the sets consists of voxels of equal dimensions, the two or more sets of 3D voxels including a set of first voxels of a first size and a set of second voxels of a second size, said second size different to said first size; and generating a voxels classification output by assigning to said voxels one or more class probabilities of a voxel to contain a fracture by classifying each of said voxels in each set in the context of the surrounding voxels.

Claims (3)

WHAT IS CLAIMED IS:
1. A three-dimensional medical image analysis system for predicting the presence of a vertebral fracture in a subject, comprising: a 3D image processor configured to receive and process 3D image data of said subject, 5 thereby producing two or more sets of 3D voxels, wherein each of the sets corresponds to the entire said 3D image, and wherein each of the sets consists of voxels of equal dimensions, the two or more sets of 3D voxels including a set of first voxels of a first size and a set of second voxels of a second size, said second size different to said first size; 10 a voxel classifier configured to generate a voxels classification output by assigning to said voxels one or more class probabilities of a voxel to contain a fracture by classifying each of said voxels in each set in the context of the surrounding voxels using a computational model; and a fracture probability estimator configured to use the voxels classification output to 15 estimate the probability of the presence of a vertebral fracture in said subject.
2. The system of claim 1 additionally comprising a spinal cord detector configured to detect a part of said 3D image data comprising the spinal cord. 20
3. The system of claim 1 or 2, wherein the voxel classifier is configured to classify each of the voxels in the first set in the context of 30-40 mm of said voxels and each of the voxels in the second set in the context of 90-
NZ764955A 2018-11-29 Three-dimensional medical image analysis method and system for identification of vertebral fractures NZ764955B2 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GBGB1720059.3A GB201720059D0 (en) 2017-12-01 2017-12-01 Three-dimensional medical image analysis method and system for identification of vertebral fractures
PCT/EP2018/082925 WO2019106061A1 (en) 2017-12-01 2018-11-29 Three-dimensional medical image analysis method and system for identification of vertebral fractures

Publications (2)

Publication Number Publication Date
NZ764955A NZ764955A (en) 2023-11-24
NZ764955B2 true NZ764955B2 (en) 2024-02-27

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