Jun 6, 2018 · In this paper, we present a CAD tool for automatic classification of tissue malignancy based on some colour and texture features of histological ...
A CAD tool for automated malignancy assessment of breast tissue histological images into four classes: normal, benign, in situ and invasive, which yields ...
In this article we propose a CAD tool for automated malignancy assessment of breast tissue histological images into four classes: normal, benign, in situ and ...
In this article we propose a CAD tool for automated malignancy assessment of breast tissue histological images into four classes: normal, benign, in situ and ...
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Automatic Breast Cancer Grading of Histological Images Based on Colour and Texture Descriptors · List of references · Publications that cite this publication.
Breast Cancer Histopathological Images Recognition Based on Low ...
pmc.ncbi.nlm.nih.gov › PMC8236881
Jun 14, 2021 · 16 morphological features were extracted, and 8 classifiers were used for recognition, the accuracy is about 80%. The authors in (12–14) ...
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This paper has described a complete study on breast TMA classification using the combination of colour and texture descriptors. The study shows promising ...
To identify histological grades in breast cancer images, we developed an automated grading of nuclei using unsupervised feature extraction. Our major ...
A novel image analysis methodology for automatically distinguishing low and high grades of breast cancer from digitized histopathology is presented and the ...
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Sep 3, 2018 · Most automated analyses of histology images use features that describe the properties of cells such as statistics of shape and color.
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