FR3142275B1 - Method for automatic segmentation of an organ on a three-dimensional medical image - Google Patents
Method for automatic segmentation of an organ on a three-dimensional medical image Download PDFInfo
- Publication number
- FR3142275B1 FR3142275B1 FR2212085A FR2212085A FR3142275B1 FR 3142275 B1 FR3142275 B1 FR 3142275B1 FR 2212085 A FR2212085 A FR 2212085A FR 2212085 A FR2212085 A FR 2212085A FR 3142275 B1 FR3142275 B1 FR 3142275B1
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- organ
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- medical image
- dimensional medical
- automatic segmentation
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/752—Contour matching
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/143—Segmentation; Edge detection involving probabilistic approaches, e.g. Markov random field [MRF] modelling
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/149—Segmentation; Edge detection involving deformable models, e.g. active contour models
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/74—Image or video pattern matching; Proximity measures in feature spaces
- G06V10/75—Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video features; Coarse-fine approaches, e.g. multi-scale approaches; using context analysis; Selection of dictionaries
- G06V10/755—Deformable models or variational models, e.g. snakes or active contours
- G06V10/7553—Deformable models or variational models, e.g. snakes or active contours based on shape, e.g. active shape models [ASM]
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/60—Type of objects
- G06V20/64—Three-dimensional objects
- G06V20/653—Three-dimensional objects by matching three-dimensional models, e.g. conformal mapping of Riemann surfaces
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06T2207/10088—Magnetic resonance imaging [MRI]
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
- G06T2207/30081—Prostate
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/03—Recognition of patterns in medical or anatomical images
- G06V2201/031—Recognition of patterns in medical or anatomical images of internal organs
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- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- Software Systems (AREA)
- General Physics & Mathematics (AREA)
- Multimedia (AREA)
- Evolutionary Computation (AREA)
- Databases & Information Systems (AREA)
- Medical Informatics (AREA)
- General Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Probability & Statistics with Applications (AREA)
- Apparatus For Radiation Diagnosis (AREA)
- Magnetic Resonance Imaging Apparatus (AREA)
- Ultra Sonic Daignosis Equipment (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
- Image Analysis (AREA)
Abstract
Procédé de segmentation d’une image en trois dimensions d’au moins un organe d’un patient comprenant au moins les étapes de : extraire de l’image en trois dimensions dudit organe, une carte de probabilités qui affecte à chaque voxel de l’image une probabilité d’appartenance à un contour de l’organe sur l’image ;extraire de ladite carte de probabilités, au moins un point-cible en se basant sur ladite probabilité d’appartenance au contour de l’organe sur l’image ;à partir de chaque point-cible extrait à l’étape précédente, déformer un modèle déformable de cet organe pour obtenir la segmentation en trois dimensions dudit organe sur l’image. FIGURE DE L’ABREGE : [Fig. 1]Method for segmenting a three-dimensional image of at least one organ of a patient comprising at least the steps of: extracting from the three-dimensional image of said organ, a probability map which assigns to each voxel of the image a probability of belonging to an outline of the organ on the image; extracting from said probability map, at least one target point based on said probability of belonging to the outline of the organ on the image; from each target point extracted in the previous step, deforming a deformable model of this organ to obtain the three-dimensional segmentation of said organ on the image. FIGURE OF THE ABSTRACT: [Fig. 1]
Priority Applications (4)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| FR2212085A FR3142275B1 (en) | 2022-11-21 | 2022-11-21 | Method for automatic segmentation of an organ on a three-dimensional medical image |
| JP2025529752A JP2025537896A (en) | 2022-11-21 | 2023-11-20 | A method for automatically segmenting organs on three-dimensional medical images. |
| EP23810312.1A EP4623424A1 (en) | 2022-11-21 | 2023-11-20 | Method for automatically segmenting an organ on a three-dimensional medical image |
| PCT/EP2023/082439 WO2024110407A1 (en) | 2022-11-21 | 2023-11-20 | Method for automatically segmenting an organ on a three-dimensional medical image |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| FR2212085 | 2022-11-21 | ||
| FR2212085A FR3142275B1 (en) | 2022-11-21 | 2022-11-21 | Method for automatic segmentation of an organ on a three-dimensional medical image |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| FR3142275A1 FR3142275A1 (en) | 2024-05-24 |
| FR3142275B1 true FR3142275B1 (en) | 2024-10-04 |
Family
ID=85727230
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| FR2212085A Active FR3142275B1 (en) | 2022-11-21 | 2022-11-21 | Method for automatic segmentation of an organ on a three-dimensional medical image |
Country Status (4)
| Country | Link |
|---|---|
| EP (1) | EP4623424A1 (en) |
| JP (1) | JP2025537896A (en) |
| FR (1) | FR3142275B1 (en) |
| WO (1) | WO2024110407A1 (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN120508922B (en) * | 2025-07-22 | 2025-11-07 | 湖南坤雷科技有限公司 | Method, device, equipment and medium for dynamically zeroing and suppressing electromagnetic background noise |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9025841B2 (en) * | 2009-11-18 | 2015-05-05 | Siemens Aktiengesellschaft | Method and system for segmentation of the prostate in 3D magnetic resonance images |
-
2022
- 2022-11-21 FR FR2212085A patent/FR3142275B1/en active Active
-
2023
- 2023-11-20 WO PCT/EP2023/082439 patent/WO2024110407A1/en not_active Ceased
- 2023-11-20 JP JP2025529752A patent/JP2025537896A/en active Pending
- 2023-11-20 EP EP23810312.1A patent/EP4623424A1/en active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| JP2025537896A (en) | 2025-11-20 |
| FR3142275A1 (en) | 2024-05-24 |
| EP4623424A1 (en) | 2025-10-01 |
| WO2024110407A1 (en) | 2024-05-30 |
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Legal Events
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|---|---|---|---|
| PLFP | Fee payment |
Year of fee payment: 2 |
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| PLSC | Publication of the preliminary search report |
Effective date: 20240524 |
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| PLFP | Fee payment |
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| PLFP | Fee payment |
Year of fee payment: 4 |