Artificial intelligence and imaging for diagnostic and treatment challenges in breast care: first Deep Breast Workshop, Deep-Breath 2024 : held in conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024 : proceedings - Mann, Ritse M.; Zhang, Tianyu; Tan, Tao; Han, Luyi; Truhn, Daniel; Li, Shuo; Gao, Yuan; Doyle, Shannon; Martí Marly, Robert; Kather, Jakob Nikolas; Pinker-Domenig, Katja; Wu, Shandong; et al. (Lecture notes in computer science, 2025)
Evaluation of Bagging Ensembles on Multimodal Data for Breast Cancer Diagnosis -- HF-Fed: Hierarchical based customized Federated Learning Framework for X-Ray Imaging -- DuEU-Net: Dual Encoder UNet with Modality-Agnostic Training for PET-CT Multi-Modal Organ and Lesion Segmentation -- One for All: UNET Training on Single-Sequence Masks for Multi-Sequence Breast MRI Segmentation -- Multimodal Breast MRI Language-Image Pretraining (MLIP): An Exploration of a Breast MRI Foundation Model -- Enhancing the Utility of Privacy-Preserving Cancer Classification using Synthetic Data -- Efficient Generation of Synthetic Breast CT Slices By Combining Generative and Super-Resolution Models -- Exploring Patient Data Requirements in Training Effective AI Models for MRI-based Breast Cancer Classification -- Virtual dynamic contrast enhanced breast MRI using 2D U-Net -- Optimizing BI-RADS 4 Lesion Assessment using Lightweight Convolutional Neural Network with CBAM in Contrast Enhanced Mammography -- Mammographic Breast Positioning Assessment via Deep Learning -- Endpoint Detection in Breast Images for Automatic Classification of Breast Cancer Aesthetic Results -- Thick Slices for Optimal Digital Breast Tomosynthesis Classification with Deep-Learning -- Predicting Aesthetic Outcomes in Breast Cancer Surgery: a Multimodal Retrieval Approach -- Vision Mamba for Classification of Breast Ultrasound Images -- Breast Cancer Molecular Subtyping from H&E Whole Slide Images using Foundation Models and Transformers -- Graph Neural Networks for modelling breast biomechanical compression -- A generative adversarial approach to remove Moiré artifacts in Dark-field and Phase-contrast x-ray images -- MRI Breast tissue segmentation using nnUNet for Biomechanical modeling -- Fat-Suppressed Breast MRI Synthesis for Domain Adaptation in Tumour Segmentation -- Guiding Breast Conservative Surgery by Augmented Reality from Preoperative MRI: Initial System Design and Retrospective Trials -- ELK: Enhanced Learning through cross-modal Knowledge transfer for lesion detection in limited-sample contrast-enhanced mammography datasets -- Safe Breast Cancer Diagnosis Resilient to Mammographic Adversarial Samples.