Breast Cancer Detection

Benchmarks archive 2025-07-28

4 leaderboard tables shown for this task, 4 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

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

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 40 papers with code (126 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.

• BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis
  7 Apr 2020 8 repositories listed
  This paper describes the field research, design and comparative deployment of a multimodal medical imaging user interface for breast screening.
• Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography
  30 Aug 2017 5 repositories listed
  We also demonstrate that a whole image classifier trained using our end-to-end approach on the DDSM digitized film mammograms can be transferred to INbreast FFDM images using only a subset of the INbreast data for…
• 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.
• Evaluating Deep Learning Models for Breast Cancer Classification: A Comparative Study
  29 Aug 2024 2 repositories listed
  This study evaluates the effectiveness of deep learning models in classifying histopathological images for early and accurate detection of breast cancer.
• CEIMVEN: An Approach of Cutting Edge Implementation of Modified Versions of EfficientNet (V1-V2) Architecture for Breast Cancer Detection and Classification from Ultrasound Images
  25 Aug 2023 2 repositories listed
  In this research, we focused mostly on our rigorous implementations and iterative result analysis of different cutting-edge modified versions of EfficientNet architectures namely EfficientNet-V1 (b0-b7) and…
• Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening
  20 Mar 2019 2 repositories listed
  We present a deep convolutional neural network for breast cancer screening exam classification, trained and evaluated on over 200, 000 exams (over 1, 000, 000 images).
• High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks
  21 Mar 2017 2 repositories listed
  In our work, we propose to use a multi-view deep convolutional neural network that handles a set of high-resolution medical images.
• Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
  24 Jun 2025 1 repository listed
  However, the optimal approach for explicit alignment in mammography remains underexplored.
• A Multi-Modal AI System for Screening Mammography: Integrating 2D and 3D Imaging to Improve Breast Cancer Detection in a Prospective Clinical Study
  8 Apr 2025 1 repository listed
  An improved version, trained on over 750, 000 exams with additional labels, further reduced the gap by 18.
• QTSeg: A Query Token-Based Architecture for Efficient 2D Medical Image Segmentation
  23 Dec 2024 1 repository listed
  Conversely, transformer architectures leverage attention mechanisms to excel in handling long-range dependencies.
• Multi-Tiered Self-Contrastive Learning for Medical Microwave Radiometry (MWR) Breast Cancer Detection
  6 Oct 2024 1 repository listed
  This study introduces a novel multi-tiered self-contrastive model tailored for microwave radiometry (MWR) in breast cancer detection.
• BCDNet: A Fast Residual Neural Network For Invasive Ductal Carcinoma Detection
  25 Aug 2024 1 repository listed
  It is of great significance to diagnose Invasive Ductal Carcinoma (IDC) in early stage, which is the most common subtype of breast cancer.
• Snuffy: Efficient Whole Slide Image Classifier
  15 Aug 2024 1 repository listed
  Our sparsity pattern is tailored for pathology and is theoretically proven to be a universal approximator with the tightest probabilistic sharp bound on the number of layers for sparse transformers, to date.
• 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.
• Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data
  17 Jul 2024 1 repository listed
  This work addresses these challenges exploring and quantifying the utility of privacy-preserving deep learning techniques, concretely, (i) differentially private stochastic gradient descent (DP-SGD) and (ii) fully…
• Mitigating annotation shift in cancer classification using single image generative models
  30 May 2024 1 repository listed
  However, the success of AI applications in this domain is restricted by the quantity and quality of available data, posing challenges due to limited and costly data annotation procedures that often lead to annotation…
• Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography
  20 May 2024 1 repository listed
  The lack of large and diverse training data on Computer-Aided Diagnosis (CAD) in breast cancer detection has been one of the concerns that impedes the adoption of the system.
• 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.
• A Study of Acquisition Functions for Medical Imaging Deep Active Learning
  28 Jan 2024 1 repository listed
  In this work, we show how active learning could be very effective in data scarcity situations, where obtaining labeled data (or annotation budget is very limited).
• Screening Mammography Breast Cancer Detection
  21 Jul 2023 1 repository listed
  Breast cancer is a leading cause of cancer-related deaths, but current programs are expensive and prone to false positives, leading to unnecessary follow-up and patient anxiety.
• Synthesis of Contrast-Enhanced Breast MRI Using Multi-b-Value DWI-based Hierarchical Fusion Network with Attention Mechanism
  3 Jul 2023 1 repository listed
  DWIs with different b-values are fused to efficiently utilize the difference features of DWIs.
• High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection
  20 Sep 2022 1 repository listed
  Computer-aided detection systems based on deep learning have shown good performance in breast cancer detection.
• Classification of Breast Tumours Based on Histopathology Images Using Deep Features and Ensemble of Gradient Boosting Methods
  3 Sep 2022 1 repository listed
  The Inception-ResNet-v2 which has both residual and inception networks profits together has shown the best feature extraction capability in the case of breast cancer histopathology images among all tested CNNs.
• A simple normalization technique using window statistics to improve the out-of-distribution generalization on medical images
  7 Jul 2022 1 repository listed
  In this study, we present a novel normalization technique called window normalization (WIN) to improve the model generalization on heterogeneous medical images, which is a simple yet effective alternative to existing…
• 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…
• Meta-repository of screening mammography classifiers
  10 Aug 2021 1 repository listed
  Artificial intelligence (AI) is showing promise in improving clinical diagnosis.
• Memory-aware curriculum federated learning for breast cancer classification
  6 Jul 2021 1 repository listed
  Our curriculum controls the order of the training samples paying special attention to those that are forgotten after the deployment of the global model.
• XBNet : An Extremely Boosted Neural Network
  9 Jun 2021 1 repository listed
  Neural networks have proved to be very robust at processing unstructured data like images, text, videos, and audio.
• Machine Learning-Based Approaches For Breast Cancer Detection in Microwave Imaging
  10 Feb 2021 1 repository listed
  Microwave imaging is a promising detection tool for harmless and non-ionizing screening of breast cancer.

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.