Breast Cancer Histology Image Classification

Benchmarks archive 2025-07-28

2 leaderboard tables shown for this task, 2 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

2 subtasks in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

12 shown of 12 papers with code (17 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis
  2 Feb 2018 3 repositories listed Syntology ran 4 of 4 samples · 0 unverified · 3 pointer-only (licence)
  In this work, we develop the computational approach based on deep convolution neural networks for breast cancer histology image classification.
• Breast-NET: a lightweight DCNN model for breast cancer detection and grading using histological samples
  10 Aug 2024 1 repository listed
  Experimental results show that our framework outperforms state-of-the-art approaches in terms of accuracy, space, and computational complexity for the BreakHis, IDC grading, and IDC datasets.
• Which Backbone to Use: A Resource-efficient Domain Specific Comparison for Computer Vision
  9 Jun 2024 1 repository listed
  In contemporary computer vision applications, particularly image classification, architectural backbones pre-trained on large datasets like ImageNet are commonly employed as feature extractors.
• Classification of Breast Cancer Histopathology Images using a Modified Supervised Contrastive Learning Method
  6 May 2024 1 repository listed
  Deep neural networks have reached remarkable achievements in medical image processing tasks, specifically in classifying and detecting various diseases.
• BCI: Breast Cancer Immunohistochemical Image Generation through Pyramid Pix2pix
  25 Apr 2022 1 repository listed
  The evaluation of human epidermal growth factor receptor 2 (HER2) expression is essential to formulate a precise treatment for breast cancer.
• VGGIN-Net: Deep Transfer Network for Imbalanced Breast Cancer Dataset
  29 Mar 2022 1 repository listed
  In this paper, we have presented a novel deep neural network architecture involving transfer learning approach, formed by freezing and concatenating all the layers till block4 pool layer of VGG16 pre-trained model (at…
• Magnification Prior: A Self-Supervised Method for Learning Representations on Breast Cancer Histopathological Images
  15 Mar 2022 1 repository listed
  This work presents a novel self-supervised pre-training method to learn efficient representations without labels on histopathology medical images utilizing magnification factors.
• MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification
  24 Aug 2021 1 repository listed
  It exploits the high sensitivity to the multi-level contextual information using an uncertainty quantification component to accomplish a novel dynamic ensemble model.
• Magnification Generalization for Histopathology Image Embedding
  18 Jan 2021 1 repository listed
  However, a useful task in histopathology embedding is to train an embedding space regardless of the magnification level.
• Regression Concept Vectors for Bidirectional Explanations in Histopathology
  9 Apr 2019 1 repository listed
  Explanations for deep neural network predictions in terms of domain-related concepts can be valuable in medical applications, where justifications are important for confidence in the decision-making.
• Breast cancer histology classification using Deep Residual Networks
  1 Jul 2018 1 repository listed
  In this work, in order to improve the computer aided diagnosis systems’ performance on histopathological image analysis, we have proposed an approach with image pre-processing followed by a deep learning method to…
• Two-Stage Convolutional Neural Network for Breast Cancer Histology Image Classification
  11 Mar 2018 1 repository listed
  This paper explores the problem of breast tissue classification of microscopy images.

Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.