mlsanityData to 14 Oct 2026

Machine Learning Methods for Histopathological Image Analysis: A Review

arXiv 2102.03889 ↗First posted 7 Feb 2021cs.CVcited by 10

Not on the map. Why?

Abstract (arXiv)

Histopathological images (HIs) are the gold standard for evaluating some types of tumors for cancer diagnosis. The analysis of such images is not only time and resource consuming, but also very challenging even for experienced pathologists, resulting in inter- and intra-observer disagreements. One of the ways of accelerating such an analysis is to use computer-aided diagnosis (CAD) systems. In this paper, we present a review on machine learning methods for histopathological image analysis, including shallow and deep learning methods. We also cover the most common tasks in HI analysis, such as segmentation and feature extraction. In addition, we present a list of publicly available and private datasets that have been used in HI research.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 21 of its 219 references that are in the map. First posted on arXiv 7 Feb 2021.

Builds on

21 of 219 references.

References · 21

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2014Very Deep Convolutional Networks for Large-Scale Image Recognitioncited by 15,364
  3. 2016Densely Connected Convolutional Networkscited by 6,720
  4. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,475
  5. 2014Going Deeper with Convolutionscited by 4,241
  6. 2017MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applicationscited by 3,845
  7. 2016Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learningcited by 1,512
  8. 2017A Survey on Deep Learning in Medical Image Analysiscited by 1,186
  9. 2018BACH: Grand Challenge on Breast Cancer Histology Imagescited by 131
  10. 2017Machine learning methods for histopathological image analysiscited by 79
  11. 2020A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networkscited by 25
  12. 2017The importance of stain normalization in colorectal tissue classification with convolutional networkscited by 20
9 more
  1. 2014Assessment of algorithms for mitosis detection in breast cancer histopathology imagescited by 16
  2. 2019Automated Classification of Histopathology Images Using Transfer Learningcited by 14
  3. 2016Gland Instance Segmentation Using Deep Multichannel Neural Networkscited by 11
  4. 2019Classification of Histopathological Biopsy Images Using Ensemble of Deep Learning Networkscited by 11
  5. 2017Sparse Autoencoder for Unsupervised Nucleus Detection and Representation in Histopathology Imagescited by 10
  6. 2017Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology imagescited by 8
  7. 2020Data Augmentation for Histopathological Images Based on Gaussian-Laplacian Pyramid Blendingcited by 7
  8. 2019Double Transfer Learning for Breast Cancer Histopathologic Image Classificationcited by 6
  9. 2019Texture CNN for Histopathological Image Classificationcited by 5

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 1; 2022: 2; 2023: 1; 2024: 3; 2025: 2; 2026: 1.

10 papers.

  1. 2021BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Imagescited by 132
  2. 2024Self-Supervised Representation Learning for Nerve Fiber Distribution Patterns in 3D-PLIcited by 4
  3. 2022Texture Characterization of Histopathologic Images Using Ecological Diversity Measures and Discrete Wavelet Transformcited by 1
  4. 2023Automatic Data Augmentation Learning using Bilevel Optimization for Histopathological Imagescited by 1
  5. 2026Unmasking Biases and Reliability Concerns in Convolutional Neural Networks Analysis of Cancer Pathology Imagescited by 1
  6. 2022Multiscale Analysis for Improving Texture Classificationcited by 0
  7. 2024Automatic Labels are as Effective as Manual Labels in Biomedical Images Classification with Deep Learningcited by 0
  8. 2024Deep Learning for Classification of Inflammatory Bowel Disease Activity in Whole Slide Images of Colonic Histopathologycited by 0
  9. 2025CREATE-FFPE: Cross-Resolution Compensated and Multi-Frequency Enhanced FS-to-FFPE Stain Transfer for Intraoperative IHC Imagescited by 0
  10. 2025Challenges in Deep Learning-Based Small Organ Segmentation: A Benchmarking Perspective for Medical Research with Limited Datasetscited by 0