Breast Cancer Histology Image Classification
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Benchmarks
Most implemented
Breast-NET: a lightweight DCNN model for breast cancer detection and grading using histological samples
Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision
Classification of Breast Cancer Histopathology Images using a Modified Supervised Contrastive Learning Method
VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer Dataset
Papers
Breast-NET: a lightweight DCNN model for breast cancer detection and grading using histological samples
Breast cancer is a prevalent and highly lethal cancer affecting women globally. While non-invasive techniques like ultrasound and mammogram are used for diagnosis, histological examination after biopsy is considered the …
Breast Cancer DetectionBreast Cancer Histology Image ClassificationGPUImage Classification+1Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision
In contemporary computer vision applications, particularly image classification, architectural backbones pre-trained on large datasets like ImageNet are commonly employed as feature extractors. Despite the widespread use…
Breast Cancer Histology Image ClassificationDecision Makingimage-classificationImage Classification+1Classification of Breast Cancer Histopathology Images using a Modified Supervised Contrastive Learning Method
Deep neural networks have reached remarkable achievements in medical image processing tasks, specifically in classifying and detecting various diseases. However, when confronted with limited data, these networks face a c…
Breast Cancer DetectionBreast Cancer Histology Image ClassificationClassification Of Breast Cancer Histology ImagesContrastive Learning+3Rotation-Agnostic Image Representation Learning for Digital Pathology
This paper addresses complex challenges in histopathological image analysis through three key contributions. Firstly, it introduces a fast patch selection method, FPS, for whole-slide image (WSI) analysis, significantly …
Breast Cancer Histology Image ClassificationMedical Image RetrievalRepresentation LearningSelf-Supervised LearningAttention-Map Augmentation for Hypercomplex Breast Cancer Classification
Breast cancer is the most widespread neoplasm among women and early detection of this disease is critical. Deep learning techniques have become of great interest to improve diagnostic performance. However, distinguishing…
Breast Cancer Histology Image ClassificationBreast Tumour ClassificationCancer ClassificationClassification+2Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers
Convolution Neural Networks (CNNs) are widely used in medical image analysis, but their performance degrade when the magnification of testing images differ from the training images. The inability of CNNs to generalize ac…
Breast Cancer Histology Image ClassificationDeep LearningImage ClassificationMedical Image Analysis