Xu et al., 2015 - Google Patents
Efficient multi-atlas abdominal segmentation on clinically acquired CT with SIMPLE context learningXu et al., 2015
View HTML- Document ID
- 12286630692905583327
- Author
- Xu Z
- Burke R
- Lee C
- Baucom R
- Poulose B
- Abramson R
- Landman B
- Publication year
- Publication venue
- Medical image analysis
External Links
Snippet
Abdominal segmentation on clinically acquired computed tomography (CT) has been a challenging problem given the inter-subject variance of human abdomens and complex 3-D relationships among organs. Multi-atlas segmentation (MAS) provides a potentially robust …
- 230000011218 segmentation 0 title abstract description 78
Classifications
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- G06T2207/30004—Biomedical image processing
- G06T2207/30048—Heart; Cardiac
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
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- G06T2207/10088—Magnetic resonance imaging [MRI]
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- G06T2207/10104—Positron emission tomography [PET]
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- G06T2207/20101—Interactive definition of point of interest, landmark or seed
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- 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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- G—PHYSICS
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- G06T3/0068—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image for image registration, e.g. elastic snapping
- G06T3/0081—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image for image registration, e.g. elastic snapping by elastic snapping
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