Mammography

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8 papers in the last four weeks, up 100% on the four weeks before. 0.1% of all new papers.

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Healthy Counterfactual Generation via Diffusion Inpainting for Mammography Classification
Oct 8, 2026Inês Cruchinho Garcia, Mariana Mourão, Francisco Maria Calisto +2Counterfactual Data Augmentation Mammography
Institute for Systems and Robotics, Instituto Superior Técnico, Lisbon, Portugal
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 Cancer Medical Image Classification
Mekelle University, Mekelle, Ethiopia · Clinical Oncologist London School of Hygiene and Tropical Medicine London, UK
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 Classification Medical Imaging Foundation Models
Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA · University of Maryland, College Park, MD, USA
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 Extraction LLM 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
MammoClaw: Towards Skill-Evolving Agent Harness for Breast Cancer Mammography Analysis
Sep 25, 2026Krishna Kanth NakkaTool-Using Agents LLM Agent Harnesses
Munich, Bavaria, Germany
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 Fusion Medical Image Classification
Shenzhen Loop Area Institute, Shenzhen, China · The Chinese University of Hong Kong, Shenzhen, China · Shenzhen Research Institute of Big Data, Shenzhen, China
Foundation model embeddings capture pre-diagnostic changes on screening mammograms
Sep 22, 2026Kalina P. Slavkova, Eric Brattain, Aditya Gowd +6Breast Cancer Medical Imaging Foundation Models
HOPPR, Chicago, IL, USA · University of Utah School of Medicine, Salt Lake City, UT, USA · 4DMedical, Woodland Hills, CA, USA +1
Mammo-LIFE: Longitudinal Mammographic Imaging and Clinical Feature Enrichment for Post-Radiotherapy Outcome Prediction
Sep 22, 2026Farnoush Bayatmakou, Maryam Hosseini, Reza Taleei +1Clinical Outcome Prediction Longitudinal 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
Mammography Foundation Models for Opportunistic Prediction of Major Adverse Cardiovascular Events
Sep 16, 2026Paula Feldman, Nusrat Binta Nizam, Sunwoo Kwak +3Medical Imaging Foundation Models Clinical Outcome Prediction
Department of Radiology, Weill Cornell Medicine, New York, NY, USA · Cornell Tech, New York, NY, USA · Cornell University, New York, NY, USA
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 VLMs Mammography
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
TRUST: Threshold-Recalibrated Uncertainty-Safe Training for Certified Dismissal in Breast Cancer Screening
Aug 31, 2026Parham Hajishafiezahramini, Matthew Hamilton, Edward Kendall +2Breast Cancer Selective 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
MammoMix: Leveraging Mixture of Experts for Robust Mammogram Breast Detection
Aug 11, 2026Dinh Tan Nguyen, Hoang Quan Dang, Chen Zhang +1Domain Generalization Mammography
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
BreastMammo and DenseMammo: Benchmarks for Mammography Domain Generalization
Aug 10, 2026Hongyi Pan, Gorkem Durak, Halil Ertugrul Aktas +18Domain Generalization Medical Image Classification
Northwestern University · University of Wisconsin-Madison · Istanbul University +7
Modern Backbones Improve Multi-task DETR for Mammography Classification and Lesion Localization
Aug 10, 2026Dinh Tan Nguyen, Quang-Hien Kha, Le-Hoang Nguyen +8Detection Transformer Multi-Task Learning
University of Technology Sydney, Australia. · Saigon Precision Medicine Research Center, Vietnam. · College of Medicine, Taipei Medical University, Taiwan. +3
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 Learning Medical Image Classification
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany · Siemens Healthineers, Erlangen, Germany
Gradient-Based Latent Decomposition Reveals Mechanisms of Feature Degradation in Weakly Supervised Mammography
Jul 24, 2026Vinceline Bertrand, Ionut CardeiVariational Autoencoders Hierarchical Representation Learning
Florida Atlantic University, Boca Raton, FL, USA
A Diagnostic Gap Framework for Evaluating Reconstruction Fidelity in Weakly Supervised Mammography
Jul 22, 2026Vinceline Bertrand, Ionut CardeiImage Reconstruction Weakly Supervised Learning
Florida Atlantic University · Boca Raton, FL, USA
Region-Grounded Vision-Language Learning for Detection-Guided Mammographic Lesion Classification
Jul 17, 2026Zhengbo Zhou, Jiren Li, Dooman Arefan +2Radiology VLMs Vision-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
Longitudinal Multi-View Breast Cancer Risk Prediction
Jul 13, 2026Solveig Thrun, Zijun Sun, Suaiba A. Salahuddin +5Breast Cancer Longitudinal 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
Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift
Jul 11, 2026Giang Nguyen, Raghav Mehta, Emma A. M. Stanley +4Distribution Shift Robustness Medical 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
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 Learning Medical 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
Unsupervised Domain Adaptation for Calcification Classification in Mammography Across Multi-Site Datasets
Jul 7, 2026Xuan Liu, Derek L. Nguyen, Emily C. Barre +7Unsupervised Domain Adaptation Mammography
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
AEGIS: A Multi-Task Joint-Embedding Predictive Architecture for Mammography
Jun 30, 2026Scott Chase Waggener, Sai Karthik Navuluru, Lakshman TamilBreast Cancer Joint-Embedding Predictive Architecture
Department of Electrical and Computer Engineering University of Texas at Dallas Richardson, TX
MammoFlow: Multiview Mammogram Synthesis with Anatomically Consistent Flow Matching
Jun 26, 2026Yuexi Du, Leya Barrientos, Laura Sheiman +3Multi-View Consistency Mammography
Department of Biomedical Engineering, Yale University · Department of Radiology & Biomedical Imaging, Yale University
Revealing Mammographic Phenotypes in Deep Learning Breast Cancer Risk Models
Jun 24, 2026Ruiyu Jia, Yanqi Xu, Yuxuan Chen +2Breast Cancer Medical 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
BAC-JEPA: Label-Efficient Breast Arterial Calcification Segmentation via Synthetic Mammography-Guided Supervision
Jun 20, 2026Scott Chase Waggener, Lakshman TamilSynthetic Data Augmentation Medical Imaging
Department of Computer Engineering University of Texas at Dallas Richardson, TX
MammoExpert: Benchmarking Chain-of-Thought Reasoning in Mammography Diagnosis
Jun 19, 2026Di Dai, Bo Liu, Youcheng Li +9Medical Imaging CoT Reasoning
State Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University Beijing, China · School of Computer Science and Engineer, Beijing University of Aeronautics and Astronautics Beijing, China · Center for Data Science, Peking University Beijing, China +5
DSU-Net: An Attention-Enhanced Dense Skip U-Net for Breast Lesion Segmentation in Mammographic Images
Jun 3, 2026Reza Bozorgpour, Mohammadreza Soltany SadrabadiMedical Imaging U-Net
Department of Biomedical Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI, USA · Department of Mechanical Engineering, Northern Arizona University, Flagstaff, AZ, USA
BreastGPT: A Multimodal Large Language Model for the Full Spectrum of Breast Cancer Clinical Routine
Jun 3, 2026Yang Liu, Jiajin Zhang, Danyang Tu +8Breast Cancer Medical Imaging
DAMO Academy, Alibaba Group · Zhejiang University · West China Hospital +1
Cross-Modal Clinical Knowledge Integration for Mammography Report Generation
May 29, 2026Jiayi Zhu, Fuxiang Huang, Yu Xie +7Radiology Report Generation Medical Imaging
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, Guangdong, China · Lingnan University, Hong Kong, China · The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, Yunnan, China +4

Oct 8, 2026, cs.CVJ/K move · Enter open · S save

Healthy Counterfactual Generation via Diffusion Inpainting for Mammography Classification

Inês Cruchinho Garcia, Mariana Mourão, Francisco Maria Calisto, Carlos Santiago+1

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

Counterfactual Data Augmentation Mammography Medical Image Classification Medical Image Synthesis

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False negatives remain a critical limitation of computer-aided diagnosis (CAD) systems for breast cancer screening due to delayed detection and treatment. To address this issue, we propose a counterfactual data augmentation strategy that generates healthy mammograms by "erasing" lesions from anomalous images, thereby enriching the training distribution. We train a Denoising Diffusion Probabilistic Model on BI-RADS 1 (healthy) mammograms and use a RePaint-based sampling strategy to inpaint realistic normal tissue within annotated lesion bounding boxes. The resulting healthy counterfactuals replace annotated lesion regions with realistic healthy tissue while preserving patient-specific anatomical structure, as supported by similarity metrics between real and generated images. Image realism was further assessed by radiologists and found to be consistent with the original dataset quality. We evaluate counterfactual augmentation across four representative classifier architectures: a convolutional neural network (ConvNeXt), a vision transformer (ViT), a vision-language model pre-trained on mammogram-report pairs (Mammo-CLIP) and a multi-scale attention-based multiple-instance learning framework (FPN-MIL). Experiments conducted on the VinDr-Mammo dataset show improvements in sensitivity across all architectures, particularly at 80% fixed specificity, contributing towards more reliable CAD systems for breast cancer. Code is available at: https://github.com/ines03garcia/diffusion-based-counterfactual-generation.