Tootfinder

REN: Anatomically-Informed Mixture-of-Experts for Interstitial Lung Disease Diagnosis
Alec K. Peltekian, Halil Ertugrul Aktas, Gorkem Durak, Kevin Grudzinski, Bradford C. Bemiss, Carrie Richardson, Jane E. Dematte, G. R. Scott Budinger, Anthony J. Esposito, Alexander Misharin, Alok Choudhary, Ankit Agrawal, Ulas Bagci
https://arxiv.org/abs…

REN: Anatomically-Informed Mixture-of-Experts for Interstitial Lung Disease Diagnosis
Mixture-of-Experts (MoE) architectures have significantly contributed to scalable machine learning by enabling specialized subnetworks to tackle complex tasks efficiently. However, traditional MoE systems lack domain-specific constraints essential for medical imaging, where anatomical structure and regional disease heterogeneity strongly influence pathological patterns. Here, we introduce Regional Expert Networks (REN), the first anatomically-informed MoE framework tailored specifically for med…

MammoDINO: Anatomically Aware Self-Supervision for Mammographic Images
Sicheng Zhou, Lei Wu, Cao Xiao, Parminder Bhatia, Taha Kass-Hout
https://arxiv.org/abs/2510.11883 https://…

MammoDINO: Anatomically Aware Self-Supervision for Mammographic Images
Self-supervised learning (SSL) has transformed vision encoder training in general domains but remains underutilized in medical imaging due to limited data and domain specific biases. We present MammoDINO, a novel SSL framework for mammography, pretrained on 1.4 million mammographic images. To capture clinically meaningful features, we introduce a breast tissue aware data augmentation sampler for both image-level and patch-level supervision and a cross-slice contrastive learning objective that l…

High-speed proton therapy within a short breath-hold
Vivek Maradia, Nick Yue, Adam Molzahn, Jingqian Wang, Mark Pankuch, Serdar Charyyev, Billy W. Loo Jr
https://arxiv.org/abs/2510.06766

High-speed proton therapy within a short breath-hold
Proton therapy provides superior dose conformity compared with photon radiotherapy, concentrating radiation within the tumor while sparing adjacent healthy tissue. This advantage has been most effectively realized for static tumors in anatomically stable regions, such as the head and neck. For thoracic and abdominal sites, however, physiological motion remains a critical challenge: because the proton dose distribution is highly sensitive to density variations, long delivery times relative to re…