Mammography

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Overview

Mammography uses breast X-rays to detect cancer, characterize abnormalities, and help guide decisions such as follow-up or biopsy. AI approaches include convolutional networks and vision transformers for lesion detection, segmentation, and classification, alongside vision-language models and systems that combine images with clinical information. Researchers also use multiple views and prior screening exams to estimate future risk, and explore synthetic images and self-supervised learning to reduce reliance on dense annotations. A central challenge is ensuring models generalize across hospitals, vendors, and populations; external testing and comparisons with radiologists remain important, especially for safe screening decisions.

Latest papers

CardsList

45 papers3 papers in the last four weeks, down 62% on the four weeks before. 0.0% of all new papers.

  1. MammoSeek: A Mammography Agent with selective zooming for grounded reports

    Nov 4, 2026Haoyan Ding, Qian Wang, Lixia Wang +1MammographyMedical AI Agents

    University of California, Los Angeles, Los Angeles, CA, USA · Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA

  2. Do Saliency Maps Fail Dense Breasts? A Chance-Normalized, Confounder-Aware Audit of Explanation Fairness in Mammography

    Nov 4, 2026Ahmed JaheenSaliency Map EvaluationExplainable Medical Image Analysis

    New York University, New York, NY, USA

  3. Impact of Input Resolution in Mammographic Mass Detection: A Controlled Multi-Architecture Study

    Nov 3, 2026Kaan Buyukdemirci, Emine Ulku SaritasMedical Image Object DetectionMammography

    Department of Electrical and Electronics Engineering, Bilkent University, Ankara 06800, Turkey · National Magnetic Resonance Research Center (UMRAM), Bilkent University, Ankara 06800, Turkey

  4. Explicitly Aligned Multi-View Breast Cancer Risk Prediction from Variable-Length Screening Histories

    Oct 12, 2026Solveig Thrun, Zijun Sun, Suaiba A. Salahuddin +5Breast CancerMammography

    Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, 9037, Norway · SPKI The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, 9019, Norway · Norwegian Computing Center, Oslo, 0373, Norway +1

  5. Healthy Counterfactual Generation via Diffusion Inpainting for Mammography Classification

    Oct 8, 2026Inês Cruchinho Garcia, Mariana Mourão, Francisco Maria Calisto +2Mammography Image ClassificationCounterfactual Data Augmentation

    Institute for Systems and Robotics, Instituto Superior Técnico, Lisbon, Portugal

  6. Hybrid Cross-Modal Attention Network for Early Breast Cancer Detection in Low-Resource Clinical Settings

    Oct 5, 2026Simon Hadush Nrea, Filimon Gidey Gebremichael, Gebrekirstos Hagos Gebrekirstos +1Breast CancerMedical Image Classification

    Mekelle University, Mekelle, Ethiopia · Clinical Oncologist London School of Hygiene and Tropical Medicine London, UK

  7. Image-Based Breast Implant Detection for Mammography Dataset Curation and Near-Real-Time Deployment: Comparing Foundation Models and Task-Specific Convolutional Models

    Oct 1, 2026Vasisht Ishwar, Hari Trivedi, Young Seok Jeon +5Medical Image ClassificationMammography Image Classification

    Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA · University of Maryland, College Park, MD, USA

  8. Extraction of clinical findings from mammography and breast ultrasound reports: a comparison between specialists and Artificial Intelligence

    Sep 25, 2026Lorenzo Farias, Hanna Reckziegel, Daniela Duarte da Silva Bagatini +8Clinical Information ExtractionLLM Information Extraction

    Department of Engineering, Architecture and Computing, Universidade de Santa Cruz do Sul (UNISC), Santa Cruz do Sul, RS, Brazil · Graduate Program in Industrial Systems and Processes (PPGSPI), Universidade de Santa Cruz do Sul (UNISC), Santa Cruz do Sul, RS, Brazil · Graduate Program in Production and Systems Engineering (PPGEPS), Universidade do Vale do Rio dos Sinos (UNISINOS), São Leopoldo, RS, Brazil +4

  9. MammoClaw: Towards Skill-Evolving Agent Harness for Breast Cancer Mammography Analysis

    Sep 25, 2026Krishna Kanth NakkaTool-Using AgentsLLM Agent Harnesses

    Munich, Bavaria, Germany

  10. M3D-Net: Hierarchical Coordination of Spatial Context, Feature Reuse, and Differential Attention for Mammography Classification

    Sep 23, 2026Zheng Yu, Xinhang Li, Jiabao Gao +2Multi-Scale Feature FusionMedical Image Classification

    Shenzhen Loop Area Institute, Shenzhen, China · The Chinese University of Hong Kong, Shenzhen, China · Shenzhen Research Institute of Big Data, Shenzhen, China

  11. Foundation model embeddings capture pre-diagnostic changes on screening mammograms

    Sep 22, 2026Kalina P. Slavkova, Eric Brattain, Aditya Gowd +6Breast CancerMedical Imaging Foundation Models

    HOPPR, Chicago, IL, USA · University of Utah School of Medicine, Salt Lake City, UT, USA · 4DMedical, Woodland Hills, CA, USA +1

  12. Mammo-LIFE: Longitudinal Mammographic Imaging and Clinical Feature Enrichment for Post-Radiotherapy Outcome Prediction

    Sep 22, 2026Farnoush Bayatmakou, Maryam Hosseini, Reza Taleei +1Clinical Outcome PredictionLongitudinal Medical Image Analysis

    Department of Cybersecurity and Intelligent Systems Engineering (CISE), Concordia University, Montreal, QC, Canada · Department of Radiation Oncology, Atrium Health Levine Cancer Institute, Charlotte, NC, USA

  13. Mammography Foundation Models for Opportunistic Prediction of Major Adverse Cardiovascular Events

    Sep 16, 2026Paula Feldman, Nusrat Binta Nizam, Sunwoo Kwak +3Medical Imaging Foundation ModelsClinical Outcome Prediction

    Department of Radiology, Weill Cornell Medicine, New York, NY, USA · Cornell Tech, New York, NY, USA · Cornell University, New York, NY, USA

  14. From Density to Biopsy Decisions and Malignancy Prediction: A Benchmark Study of Multimodal Large Language Models Against Radiologists in Digital and Contrast-Enhanced Mammography

    Sep 13, 2026Ali Abbasian Ardakani, Afshin Mohammadi, Taha Yusuf Kuzan +11Medical VLMsMammography Image Classification

    Department of Medicine, Faculty of Medicine and Dentistry, Danube Private University, Krems an der Donau, Austria · Department of Radiology, Faculty of Medicine, Urmia University of Medical Science, Urmia, Iran · Department of Radiology, Yeditepe University, Istanbul, Türkiye +10

  15. TRUST: Threshold-Recalibrated Uncertainty-Safe Training for Certified Dismissal in Breast Cancer Screening

    Aug 31, 2026Parham Hajishafiezahramini, Matthew Hamilton, Edward Kendall +2Breast CancerSelective Prediction

    Department of Computer Science, Memorial University of Newfoundland, Canada · 2Division of Biomedical Sciences, Faculty of Medicine, Memorial University of2026 Newfoundland, Canada · 3Cancer Care, Newfoundland and Labrador Health Services, St. John’s, NL, CanadaAug 31

  16. MammoMix: Leveraging Mixture of Experts for Robust Mammogram Breast Detection

    Aug 11, 2026Dinh Tan Nguyen, Hoang Quan Dang, Chen Zhang +1Domain GeneralizationMammography

    School of Biomedical Engineering, University of Technology Sydney · School of Computer Science, University of Technology Sydney · School of Electrical and Data Engineering, University of Technology Sydney

  17. BreastMammo and DenseMammo: Benchmarks for Mammography Domain Generalization

    Aug 10, 2026Hongyi Pan, Gorkem Durak, Halil Ertugrul Aktas +18Domain GeneralizationMedical Image Classification

    Northwestern University · University of Wisconsin-Madison · Istanbul University +7

  18. Modern Backbones Improve Multi-task DETR for Mammography Classification and Lesion Localization

    Aug 10, 2026Dinh Tan Nguyen, Quang-Hien Kha, Le-Hoang Nguyen +8Detection TransformerMulti-Task Learning

    University of Technology Sydney, Australia. · Saigon Precision Medicine Research Center, Vietnam. · College of Medicine, Taipei Medical University, Taiwan. +3

  19. Re-thinking Mammography Transfer Learning: The Dataset-Informed Transfer Learning (DITL) Framework for Breast Cancer Screening and Lesion Diagnosis

    Jul 28, 2026Adarsh Bhandary Panambur, Siming Bayer, Andreas MaierMetric LearningMedical Image Classification

    Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany · Siemens Healthineers, Erlangen, Germany

  20. Gradient-Based Latent Decomposition Reveals Mechanisms of Feature Degradation in Weakly Supervised Mammography

    Jul 24, 2026Vinceline Bertrand, Ionut CardeiVariational AutoencodersHierarchical Representation Learning

    Florida Atlantic University, Boca Raton, FL, USA

  21. A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography

    Jul 22, 2026Vinceline Bertrand, Ionut CardeiImage ReconstructionWeakly Supervised Learning

    Florida Atlantic University · Boca Raton, FL, USA

  22. Region-Grounded Vision-Language Learning for Detection-Guided Mammographic Lesion Classification

    Jul 17, 2026Zhengbo Zhou, Jiren Li, Dooman Arefan +2Radiology VLMsVision-Language Models

    Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, USA · Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA · Department of Biomedical Informatics and Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA

  23. Longitudinal Multi-View Breast Cancer Risk Prediction

    Jul 13, 2026Solveig Thrun, Zijun Sun, Suaiba A. Salahuddin +5Breast CancerLongitudinal Medical Image Analysis

    Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway · SPKI The Norwegian Centre for Clinical Artificial Intelligence, University Hospital of North Norway, Tromsø, Norway · Norwegian Computing Center, Oslo, Norway +1

  24. Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift

    Jul 11, 2026Giang Nguyen, Raghav Mehta, Emma A. M. Stanley +4Medical Image ClassificationMedical Imaging Foundation Models

    College of Engineering and Computer Science, VinUniversity, Hanoi, Vietnam · Imperial College London, London, UK · Radiology Department, Vietnam National Cancer Hospital, Hanoi, Vietnam +2

  25. BiLoG-Net: A Bi-Context Location-Guided Network for Breast Mass Segmentation and Malignancy Classification in Mammography

    Jul 11, 2026Abu Fatema Mohammad Abdun Noor, Md Imam Ahasan, Md Samiul Ahasan +3Multi-Task LearningMedical Image Classification

    Department of Software Engineering, Daffodil International University, Dhaka, Bangladesh · BricksCloud AI, Uttara, Dhaka, Bangladesh · College of Computer Science, Chongqing University, Chongqing, China +3

  26. Unsupervised Domain Adaptation for Calcification Classification in Mammography Across Multi-Site Datasets

    Jul 7, 2026Xuan Liu, Derek L. Nguyen, Emily C. Barre +7Unsupervised Domain AdaptationMammography

    Department of Electrical and Computer Engineering and the Department of Radiology, Duke University, Durham, NC, USA · Department of Radiology, Duke University, Durham, NC, USA · Duke University School of Medicine, Durham, NC, USA +3

  27. AEGIS: A Multi-Task Joint-Embedding Predictive Architecture for Mammography

    Jun 30, 2026Scott Chase Waggener, Sai Karthik Navuluru, Lakshman TamilBreast CancerJoint-Embedding Predictive Architecture

    Department of Electrical and Computer Engineering University of Texas at Dallas Richardson, TX

  28. MammoFlow: Multiview Mammogram Synthesis with Anatomically Consistent Flow Matching

    Jun 26, 2026Yuexi Du, Leya Barrientos, Laura Sheiman +3Multi-View ConsistencyMammography

    Department of Biomedical Engineering, Yale University · Department of Radiology & Biomedical Imaging, Yale University

  29. Revealing Mammographic Phenotypes in Deep Learning Breast Cancer Risk Models

    Jun 24, 2026Ruiyu Jia, Yanqi Xu, Yuxuan Chen +2Breast CancerMedical Image Analysis

    Department of Mathematics, New York University Shanghai, China · Center for Data Science, New York University, USA · Perlmutter Cancer Center, NYU Langone Health, New York, USA +1

  30. BAC-JEPA: Label-Efficient Breast Arterial Calcification Segmentation via Synthetic Mammography-Guided Supervision

    Jun 20, 2026Scott Chase Waggener, Lakshman TamilSynthetic Data AugmentationMedical Imaging

    Department of Computer Engineering University of Texas at Dallas Richardson, TX