mlsanityData to 7 Oct 2026

A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks

arXiv 2003.12255 ↗First posted 27 Mar 2020eess.IV cs.CVcited by 25

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Abstract (arXiv)

Breast cancer is one of the most common and deadliest cancers among women. Since histopathological images contain sufficient phenotypic information, they play an indispensable role in the diagnosis and treatment of breast cancers. To improve the accuracy and objectivity of Breast Histopathological Image Analysis (BHIA), Artificial Neural Network (ANN) approaches are widely used in the segmentation and classification tasks of breast histopathological images. In this review, we present a comprehensive overview of the BHIA techniques based on ANNs. First of all, we categorize the BHIA systems into classical and deep neural networks for in-depth investigation. Then, the relevant studies based on BHIA systems are presented. After that, we analyze the existing models to discover the most suitable algorithms. Finally, publicly accessible datasets, along with their download links, are provided for the convenience of future researchers.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 Mar 2020.

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Citing papers per year: 2021: 5; 2022: 12; 2023: 6; 2024: 0; 2025: 0; 2026: 2.

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  1. 2021TransMIL: Transformer based Correlated Multiple Instance Learning for Whole Slide Image Classificationcited by 549
  2. 2023Diagnose Like a Pathologist: Transformer-Enabled Hierarchical Attention-Guided Multiple Instance Learning for Whole Slide Image Classificationcited by 27
  3. 2021Applications of Artificial Neural Networks in Microorganism Image Analysis: A Comprehensive Review from Conventional Multilayer Perceptron to Popular Convolutional Neural Network and Potential Visual Transformercited by 14
  4. 2021A State-of-the-art Survey of Object Detection Techniques in Microorganism Image Analysis: From Classical Methods to Deep Learning Approachescited by 12
  5. 2021Machine Learning Methods for Histopathological Image Analysis: A Reviewcited by 10
  6. 2023hist2RNA: An efficient deep learning architecture to predict gene expression from breast cancer histopathology imagescited by 10
  7. 2021A State-of-the-art Survey of Artificial Neural Networks for Whole-slide Image Analysis:from Popular Convolutional Neural Networks to Potential Visual Transformerscited by 7
  8. 2022Graph Convolutional Networks for Multi-modality Medical Imaging: Methods, Architectures, and Clinical Applicationscited by 7
  9. 2022IL-MCAM: An interactive learning and multi-channel attention mechanism-based weakly supervised colorectal histopathology image classification approachcited by 7
  10. 2022Application of Transfer Learning and Ensemble Learning in Image-level Classification for Breast Histopathologycited by 6
  11. 2023SC-MIL: Sparsely Coded Multiple Instance Learning for Whole Slide Image Classificationcited by 6
  12. 2022Breast cancer detection using artificial intelligence techniques: A systematic literature reviewcited by 5
13 more
  1. 2023Dual Attention Model with Reinforcement Learning for Classification of Histology Whole-Slide Imagescited by 5
  2. 2023Breast Cancer Histopathology Image based Gene Expression Prediction using Spatial Transcriptomics data and Deep Learningcited by 5
  3. 2022EBHI:A New Enteroscope Biopsy Histopathological H&E Image Dataset for Image Classification Evaluationcited by 3
  4. 2022A Comparative Study of Gastric Histopathology Sub-size Image Classification: from Linear Regression to Visual Transformercited by 2
  5. 2022Stain Normalized Breast Histopathology Image Recognition using Convolutional Neural Networks for Cancer Detectioncited by 1
  6. 2022What Can Machine Vision Do for Lymphatic Histopathology Image Analysis: A Comprehensive Reviewcited by 1
  7. 2022A Comprehensive Survey with Quantitative Comparison of Image Analysis Methods for Microorganism Biovolume Measurementscited by 1
  8. 2022An application of Pixel Interval Down-sampling (PID) for dense tiny microorganism counting on environmental microorganism imagescited by 1
  9. 2023A Deep Analysis of Transfer Learning Based Breast Cancer Detection Using Histopathology Imagescited by 1
  10. 2022A State-of-the-art Survey of U-Net in Microscopic Image Analysis: from Simple Usage to Structure Mortificationcited by 0
  11. 2022Application of Graph Based Features in Computer Aided Diagnosis for Histopathological Image Classification of Gastric Cancercited by 0
  12. 2026XtraLight-MedMamba for Classification of Neoplastic Tubular Adenomascited by 0
  13. 2026MagViT: Interpretable Multi-Magnification Transformers with Patient-Level Model Selection for Breast Histopathologycited by 0