Chung et al., 2020 - Google Patents
Deeply self-supervised contour embedded neural network applied to liver segmentationChung et al., 2020
View PDF- Document ID
- 3788242302863136587
- Author
- Chung M
- Lee J
- Lee M
- Lee J
- Shin Y
- Publication year
- Publication venue
- Computer methods and programs in biomedicine
External Links
Snippet
Objective Herein, a neural network-based liver segmentation algorithm is proposed, and its performance was evaluated using abdominal computed tomography (CT) images. Methods A fully convolutional network was developed to overcome the volumetric image …
- 230000011218 segmentation 0 title abstract description 60
Classifications
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- G06T2207/30048—Heart; Cardiac
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- G06T2207/10104—Positron emission tomography [PET]
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- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
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- G06K9/6201—Matching; Proximity measures
- G06K9/6202—Comparing pixel values or logical combinations thereof, or feature values having positional relevance, e.g. template matching
- G06K9/6203—Shifting or otherwise transforming the patterns to accommodate for positional errors
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- G06T2207/00—Indexing scheme for image analysis or image enhancement
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- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
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