SOTAVerified

Breast Cancer Histology Image Classification

Papers

Showing 117 of 17 papers

TitleStatusHype
BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pixCode2
VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer DatasetCode1
Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological ImagesCode1
Breast-NET: a lightweight DCNN model for breast cancer detection and grading using histological samplesCode0
Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer VisionCode0
Classification of Breast Cancer Histopathology Images using a Modified Supervised Contrastive Learning MethodCode0
Rotation-Agnostic Image Representation Learning for Digital Pathology0
Attention-Map Augmentation for Hypercomplex Breast Cancer ClassificationCode0
Magnification Invariant Medical Image Analysis: A Comparison of Convolutional Networks, Vision Transformers, and Token Mixers0
MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image ClassificationCode0
Magnification Generalization for Histopathology Image EmbeddingCode0
Regression Concept Vectors for Bidirectional Explanations in HistopathologyCode0
Hierarchical ResNeXt Models for Breast Cancer Histology Image Classification0
Breast cancer histology classification using Deep Residual NetworksCode0
Two-Stage Convolutional Neural Network for Breast Cancer Histology Image ClassificationCode0
Deep Learning Framework for Multi-class Breast Cancer Histology Image Classification0
Deep Convolutional Neural Networks for Breast Cancer Histology Image AnalysisCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1WaveMixAccuracy (%)99.39Unverified
2Breast-NETAccuracy (%)98.11Unverified
3VGGIN-NetAccuracy (%)96.15Unverified
4EfficientNet-b21:1 Accuracy92.23Unverified
5WaveMixLite-224/10Accuracy (%)91.72Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-152Accuracy (% )83Unverified