Mar 4, 2020 · This paper proposes an improved deep residual neural network for the classification of breast cancer as either benign or malignant.
This paper proposes a method based on residual network and focal loss for pathological image classification of breast cancer. This method not only overcomes ...
The Application of Focal Loss in various Domains: A Survey · Enhanced dual contrast representation learning with cell separation and merging for breast cancer ...
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Aug 29, 2022 · The use of an automatic histopathological image identification system is essential for expediting diagnoses and lowering mistake rates.
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Mar 17, 2023 · In this study, an improved VGG network was used to classify the breast cancer histopathological image from intraoperative rapid frozen sections.
Sep 20, 2024 · This paper reviews relevant research progress and applies DL models to image enhancement, segmentation, and classification based on large-scale datasets from ...
May 10, 2024 · This paper proposes an approach to enhance the differentiation task between benign and malignant Breast Tumors (BT) using histopathology images from the ...
This paper proposes a breast X-ray mammography image classification model based on Convolutional Neural Network (CNN).
Dec 14, 2022 · This study utilized soft segmentation to imitate the visual focus mechanism and proposed a new segmentation–classification joint model to achieve superior ...
The eight classification recognition accuracy of the proposed fusion model on the four amplification factors of breast cancer pathological images can reach from ...