Zhou et al., 2015 - Google Patents
Automated compromised right lung segmentation method using a robust atlas-based active volume model with sparse shape composition prior in CTZhou et al., 2015
- Document ID
- 8567069066340335470
- Author
- Zhou J
- Yan Z
- Lasio G
- Huang J
- Zhang B
- Sharma N
- Prado K
- D’Souza W
- Publication year
- Publication venue
- Computerized Medical Imaging and Graphics
External Links
Snippet
To resolve challenges in image segmentation in oncologic patients with severely compromised lung, we propose an automated right lung segmentation framework that uses a robust, atlas-based active volume model with a sparse shape composition prior. The …
- 210000004072 Lung 0 title abstract description 126
Classifications
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- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10088—Magnetic resonance imaging [MRI]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10072—Tomographic images
- G06T2207/10104—Positron emission tomography [PET]
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- G06T2207/30004—Biomedical image processing
- G06T2207/30048—Heart; Cardiac
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- 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
- G06T7/0014—Biomedical image inspection using an image reference approach
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- G06—COMPUTING; CALCULATING; COUNTING
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20112—Image segmentation details
- G06T2207/20116—Active contour; Active surface; Snakes
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
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- G06T2207/20112—Image segmentation details
- G06T2207/20156—Automatic seed setting
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- G06T2207/20101—Interactive definition of point of interest, landmark or seed
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