An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization

13 February 2020

Papers citing "An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization"

44 / 44 papers shown

Title
Enhancing breast cancer detection on screening mammogram using self-supervised learning and a hybrid deep model of Swin Transformer and Convolutional Neural Network Han Chen Anne L. Martel 43 0 0 28 Apr 2025
A Multi-Modal AI System for Screening Mammography: Integrating 2D and 3D Imaging to Improve Breast Cancer Detection in a Prospective Clinical Study Jungkyu Park Jan Witowski Yanqi Xu Hari M. Trivedi J. Gichoya ... Malte Westerhoff Linda Moy Laura Heacock Alana A. Lewin Krzysztof J. Geras 28 0 0 08 Apr 2025
Flip Learning: Weakly Supervised Erase to Segment Nodules in Breast Ultrasound Yuhao Huang Ao Chang Haoran Dou X. Tao Xinrui Zhou ... Ruobing Huang Alejandro F Frangi Lingyun Bao Xin Yang Dong Ni 79 1 0 26 Mar 2025
Mammo-Clustering: A Multi-views Tri-level Information Fusion Context Clustering Framework for Localization and Classification in Mammography Shilong Yang Chulong Zhang Qi Zang Juan Yu Liang Zeng ... Yexuan Xing Xin Pan Qi Li Xiaokun Liang Yaoqin Xie 40 0 0 23 Sep 2024
Investigating the Impact of Randomness on Reproducibility in Computer Vision: A Study on Applications in Civil Engineering and Medicine Bahadır Eryılmaz Osman Alperen Koras Jorg Schlotterer Christin Seifert 21 0 0 19 Sep 2024
Prototype-based Interpretable Breast Cancer Prediction Models: Analysis and Challenges Shreyasi Pathak Jorg Schlotterer Jeroen Veltman J. Geerdink M. V. Keulen Christin Seifert 26 3 0 29 Mar 2024
Weakly supervised localisation of prostate cancer using reinforcement learning for bi-parametric MR images Martynas Pocius Wen Yan D. Barratt M. Emberton Matthew J. Clarkson Yipeng Hu Shaheer U. Saeed 32 0 0 21 Feb 2024
Quantifying Impairment and Disease Severity Using AI Models Trained on Healthy Subjects Boyang Yu Aakash Kaku Kangning Liu A. Parnandi Emily E Fokas Anita Venkatesan Natasha Pandit Rajesh Ranganath Heidi M. Schambra C. Fernandez‐Granda 19 0 0 21 Nov 2023
Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data Yiqiu Shen Jungkyu Park Frank Yeung Eliana Goldberg Laura Heacock Farah E. Shamout Krzysztof J. Geras 13 2 0 06 Nov 2023
Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models An Yan Yu-Xiang Wang Yiwu Zhong Zexue He Petros Karypis ... Chengyu Dong Amilcare Gentili Chun-Nan Hsu Jingbo Shang Julian McAuley 27 30 0 04 Oct 2023
Unsupervised discovery of Interpretable Visual Concepts Caroline Mazini Rodrigues Nicolas Boutry Laurent Najman FAtt 16 2 0 31 Aug 2023
Post-Hoc Explainability of BI-RADS Descriptors in a Multi-task Framework for Breast Cancer Detection and Segmentation Mohammad Karimzadeh Aleksandar Vakanski Min Xian Boyu Zhang 13 5 0 27 Aug 2023
M&M: Tackling False Positives in Mammography with a Multi-view and Multi-instance Learning Sparse Detector Yen Nhi Truong Vu Dan Guo Ahmed Taha Jason Su Thomas P. Matthews 17 3 0 11 Aug 2023
Improving Mass Detection in Mammography Images: A Study of Weakly Supervised Learning and Class Activation Map Methods Vicente Sampaio F. Cordeiro 14 3 0 07 Aug 2023
MammoDG: Generalisable Deep Learning Breaks the Limits of Cross-Domain Multi-Center Breast Cancer Screening Yijun Yang Shujun Wang Lihao Liu S. Hickman F. Gilbert Carola-Bibiane Schönlieb Angelica I. Aviles-Rivero 14 5 0 02 Aug 2023
MedLSAM: Localize and Segment Anything Model for 3D CT Images Wenhui Lei Xu Wei Xiaofan Zhang Kang Li Shaoting Zhang MedIm 18 3 0 26 Jun 2023
DiffMIC: Dual-Guidance Diffusion Network for Medical Image Classification Yijun Yang H. Fu Angelica I. Aviles-Rivero Carola-Bibiane Schönlieb Lei Zhu MedIm 83 48 0 19 Mar 2023
BRAIxDet: Learning to Detect Malignant Breast Lesion with Incomplete Annotations Yuanhong Chen Yuyuan Liu Chong Wang M. Elliott C. Kwok ... Yu Tian Fengbei Liu Helen Frazer Davis J. McCarthy Gustavo Carneiro 18 1 0 31 Jan 2023
Receptive Field Refinement for Convolutional Neural Networks Reliably Improves Predictive Performance Mats L. Richter C. Pal 9 3 0 26 Nov 2022
Computer-Aided Cancer Diagnosis via Machine Learning and Deep Learning: A comparative review Solene Bechelli 11 2 0 19 Oct 2022
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning Kangning Liu Weicheng Zhu Yiqiu Shen Sheng Liu N. Razavian Krzysztof J. Geras C. Fernandez‐Granda SSL 28 24 0 17 Oct 2022
An efficient deep neural network to find small objects in large 3D images Jungkyu Park Jakub Chlkedowski Stanislaw Jastrzebski Jan Witowski Yan Xu ... Melanie Wegener Linda Moy Laura Heacock B. Reig Krzysztof J. Geras MedIm 11 1 0 16 Oct 2022
Knowledge Distillation to Ensemble Global and Interpretable Prototype-Based Mammogram Classification Models Chong Wang Yuanhong Chen Yuyuan Liu Yu Tian Fengbei Liu Davis J. McCarthy M. Elliott Helen Frazer G. Carneiro 41 19 0 26 Sep 2022
Multi-view Local Co-occurrence and Global Consistency Learning Improve Mammogram Classification Generalisation Yuanhong Chen Hu Wang Chong Wang Yu Tian Fengbei Liu M. Elliott Davis J. McCarthy Helen Frazer G. Carneiro 45 19 0 21 Sep 2022
Deep is a Luxury We Don't Have Ahmed Taha Yen Nhi Truong Vu Brent Mombourquette Thomas P. Matthews Jason Su Sadanand Singh ViT MedIm 18 2 0 11 Aug 2022
Independent evaluation of state-of-the-art deep networks for mammography O. M. Velarde Lucas Parrra OOD 23 0 0 22 Jun 2022
Mammograms Classification: A Review Marawan Elbatel 15 1 0 04 Mar 2022
Multi-task fusion for improving mammography screening data classification M. Wimmer Gert Sluiter David Major Dimitrios Lenis Astrid Berg Theresa Neubauer Katja Bühler 13 8 0 01 Dec 2021
AI-Based Detection, Classification and Prediction/Prognosis in Medical Imaging: Towards Radiophenomics F. Yousefirizi P. Decazes Amine Amyar S. Ruan Babak Saboury Arman Rahmim LM&MA MedIm 26 43 0 20 Oct 2021
Recurrent Attention Models with Object-centric Capsule Representation for Multi-object Recognition Hossein Adeli Seoyoung Ahn G. Zelinsky OCL 23 3 0 11 Oct 2021
BI-RADS-Net: An Explainable Multitask Learning Approach for Cancer Diagnosis in Breast Ultrasound Images Boyu Zhang Aleksandar Vakanski Min Xian 14 11 0 05 Oct 2021
Meta-repository of screening mammography classifiers Benjamin Stadnick Jan Witowski Vishwaesh Rajiv Jakub Chledowski Farah E. Shamout Kyunghyun Cho Krzysztof J. Geras 14 11 0 10 Aug 2021
Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis Kangning Liu Yiqiu Shen Nan Wu Jakub Chledowski C. Fernandez‐Granda Krzysztof J. Geras 17 23 0 13 Jun 2021
Hard-Attention for Scalable Image Classification Athanasios Papadopoulos Pawel Korus N. Memon 60 25 0 20 Feb 2021
Vessel-CAPTCHA: an efficient learning framework for vessel annotation and segmentation Vien Ngoc Dang Francesco Galati Rosa Cortese G. Giacomo Viola Marconeto Pratek Mathur Karim Lekadir Marco Lorenzi F. Prados Maria A. Zuluaga MedIm 17 35 0 22 Jan 2021
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations Tao Wei Angelica I Aviles-Rivero Shuo Wang Yuan Huang F. Gilbert Carola-Bibiane Schönlieb C. L. P. Chen MedIm 11 14 0 20 Jan 2021
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction Anuroop Sriram Matthew Muckley Koustuv Sinha Farah E. Shamout Joelle Pineau Krzysztof J. Geras Lea Azour Y. Aphinyanaphongs N. Yakubova W. Moore MedIm 126 64 0 13 Jan 2021
Differences between human and machine perception in medical diagnosis Taro Makino Stanislaw Jastrzebski Witold Oleszkiewicz Celin Chacko Robin Ehrenpreis ... D. Sodickson Laura Heacock Linda Moy Kyunghyun Cho Krzysztof J. Geras AAML 8 26 0 28 Nov 2020
Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms Nan Wu Zhe Huang Yiqiu Shen Jungkyu Park Jason Phang ... S. G. Kim Kyunghyun Cho Laura Heacock Linda Moy Krzysztof J. Geras 11 6 0 19 Sep 2020
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department Farah E. Shamout Yiqiu Shen Nan Wu Aakash Kaku Jungkyu Park ... W. Moore Yvonne W. Lui Yindalon Aphinyanagphongs C. Fernandez‐Granda Krzysztof J. Geras 9 0 0 04 Aug 2020
Understanding the robustness of deep neural network classifiers for breast cancer screening Witold Oleszkiewicz Taro Makino Stanislaw Jastrzebski Tomasz Trzciñski Linda Moy Kyunghyun Cho Laura Heacock Krzysztof J. Geras 11 0 0 23 Mar 2020
Learning from Suspected Target: Bootstrapping Performance for Breast Cancer Detection in Mammography Li Xiao Cheng Zhu Junjun Liu Chunlong Luo Peifang Liu Yi Zhao 6 5 0 01 Mar 2020
Energy Models for Better Pseudo-Labels: Improving Semi-Supervised Classification with the 1-Laplacian Graph Energy Angelica I. Aviles-Rivero Nicolas Papadakis Ruoteng Li P. Sellars Samar M. Alsaleh R. Tan Carola-Bibiane Schönlieb 14 3 0 20 Jun 2019
Effective Approaches to Attention-based Neural Machine Translation Thang Luong Hieu H. Pham Christopher D. Manning 214 7,923 0 17 Aug 2015