Li et al., 2019 - Google Patents
Classification of breast cancer histology images using multi-size and discriminative patches based on deep learningLi et al., 2019
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- 5962659849903460357
- Author
- Li Y
- Wu J
- Wu Q
- Publication year
- Publication venue
- Ieee Access
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The diagnosis of breast cancer histology images with hematoxylin and eosin stained is non- trivial, labor-intensive and often leads to a disagreement between pathologists. Computer- assisted diagnosis systems contribute to help pathologists improve diagnostic consistency …
- 206010006187 Breast cancer 0 title abstract description 34
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- G06K9/62—Methods or arrangements for recognition using electronic means
- G06K9/6267—Classification techniques
- G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
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- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T2207/30024—Cell structures in vitro; Tissue sections in vitro
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- G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
- G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
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- G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
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- G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
- G06K9/00147—Matching; Classification
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