LC-SD: Realistic Endoscopic Image Generation with Stable Diffusion and ControlNet
Joanna Kaleta (SANO)*; Diego Dall'Alba (University of Verona); Szymon Płotka (SANO); Przemyslaw Korzeniowski (Sano – Centre for Computational Personalised Medicine)

Deep Structural Causal Model for Investigating Causality between Genotype and Clinical Phenotype in Neurological Disorders
Fanyang Yu (University of Pennsylvania)*; Rongguang Wang (University of Pennsylvania); Pratik Chaudhari (University of Pennsylvania); Christos Davatzikos (University of Pennsylvania)

On Mitigating Shortcut Learning for Fair Chest X-ray Classification
Yuzhe Yang (MIT)*; Haoran Zhang (MIT); Dina Katabi (MIT); Marzyeh Ghassemi (MIT, University of Toronto, Vector Institute)

Cancer-Net PCa-Data: An Open-Source Benchmark Dataset for Prostate Cancer Clinical Decision Support using Synthetic Correlated Diffusion Imaging Data
Hayden Gunraj (University of Waterloo); Chi-en A Tai (University of Waterloo)*; Alexander Wong (University of Waterloo)

Dual Heteroscedastic Uncertainty Estimation for Probabilistic Unsupervised Volumetric Registration of Noisy Medical Images
Xiaoran Zhang (Yale University)*; Daniel H. Pak (Yale University); Shawn Ahn (Yale University); Chenyu You (Yale University); Xiaoxiao Li (University of British Columbia); Alex Wong (Yale University); Lawrence H Staib (Yale University); James S Duncan (Yale University)

HEALNet – Improving Medical Image Analysis using Multi-Omic Context via Hybrid Early Fusion
Konstantin Hemker (University of Cambridge)*; Nikola Simidjievski (University of Cambridge ); Mateja Jamnik (University of Cambridge)

UTAR: Source-free Unsupervised Test-time Adaptation for MRI Super-Resolution
Weitong Zhang (Imperial College London)*; Jonathan Stelter (Technical University of Munich); Cheng Ouyang (Imperial College London); Dimitrios Karampinos (Technical University of Munich); Bernhard Kainz (Imperial College London, FAU Erlangen-Nürnberg)

Unveiling the Interplay Between Interpretability and Generative Performance in Medical Diffusion Models
Mischa Dombrowski (Friedrich-Alexander-Universität Erlangen-Nürnberg)*; Hadrien Reynaud (Imperial College London); Johanna P Müller ( Friedrich-Alexander-Universität Erlangen-Nürnberg); Matthew M G Baugh (Imperial College London); Bernhard Kainz (Imperial College London, FAU Erlangen-Nürnberg)

Robust semi-supervised segmentation with timestep ensembling diffusion models
Margherita Rosnati (Imperial College London)*; Melanie Roschewitz (Imperial College London); Ben Glocker (Imperial College London)

Generative AI for Medical Video De-Identification
George Leifman (Google)*; Idan Kligvasser (Verily); Itay Ravia (Verily); Michael Elad (Google); Ehud Rivlin (Google)

Exploring General Intelligence via Gated Graph Transformer in Functional Connectivity Studies
Gang Qu (Tulane University)*; Anton Orlichenko (Tulane); Junqi Wang (Cincinnati Children’s Hospital Medical Center); Gemeng Zhang (Mayo Clinic); Li Xiao (University of Science and Technology of China); Aiying Zhang (University of Virginia); Zhengming Ding (Tulane University); Yu-Ping Wang (Tulane University)

Low Rank Mixup Augmentations for Contrastive Learning of Phenotypes from Functional Connectivity
Anton Orlichenko (Tulane)*; Gang Qu (Tulane University); Ziyu Zhou (Tulane University); Anqi Liu (Tulane); Hui Shen (Tulane); Hong-Wen Deng (Tulane University); Zhengming Ding (Tulane University); Yu-Ping Wang (Tulane University)

Exploring the Hyperparameter Space of Image Diffusion Models for Echocardiogram Generation
Hadrien Reynaud (Imperial College London)*; Bernhard Kainz (Imperial College London, FAU Erlangen-Nürnberg)

AUC-mixup: Deep AUC Maximization with Mixup
Jianzhi Xu (Shandong University)*; Gang Li (Texas A&M University); Tianbao Yang (Texas A&M university )

Assessing Self-Supervised Pretraining for Multiple Lung Ultrasound Interpretation Tasks
Blake VanBerlo (David R. Cheriton School of Computer Science, University of Waterloo)*; Brian Li (University of Waterloo); Jesse Hoey (University of Waterloo); Alexander Wong (University of Waterloo)

Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images
Chi-en A Tai (University of Waterloo)*; Elizabeth L Janes (University of Waterloo); Chris Czarnecki (University of Waterloo); Alexander Wong (University of Waterloo)

Label Augmentation Method for Medical Landmark Detection in Hip Radiograph Images
Yehyun Suh (Vanderbilt University)*; Peter Chan (UT Southwestern Medical Center); Ryan Martin (Vanderbilt University Medical Center); Daniel C Moyer (Vanderbilt University)

Spectral Image-Based Diagnosis of Voice Disorders: Leveraging Spectrograms for Non-Invasive Assessment
Sangjae Lee (SK Telecom)*; Kwangsuk Lee (SK Telecom); Hansu Cho (SK Telecom); Seungmo Cho (SK Telecom); Young Min Park (Gangnam Severance Hospital); Seung Jin Lee (Hallym University); Hye Rim Chae (Gangnam Severance Hospital)

Synthetic Tumor Manipulation: With Radiomics Features
Inye Na (Sungkyunkwan University)*; Hyunjin Park (Sungkyunkwan University)

Dynamic Neural Fields for Learning Atlases of 4D Fetal MRI Time-series
Zeen Chi (ShanghaiTech University)*; Zhongxiao Cong (ShanghaiTech University); Clinton J Wang (MIT); Yingcheng Liu (MIT); Esra Abaci Turk (Boston Children's Hospital); Ellen Grant (Boston Children's Hospital); Mazdak Abulnaga (MIT); Polina Golland (MIT); Neel Dey (MIT)

RE-tune: Incremental Fine Tuning of Biomedical Vision-Language Models for Multi-label Chest X-ray Classification
Marco Mistretta (University of Florence, Italy)*; Andy Bagdanov (University of Florence, Italy)

Self-Supervised Cross-Encoder for Diagnosis of Alzheimer's Disease [supplement]
Fangqi Cheng (The University of Glasgow)*; Xiaochen Yang (University of Glasgow)

LKA: Large-kernel Attention for Efficient and Robust Brain Lesion Segmentation
Liam Chalcroft (University College London)*; Ruben Lourenço Pereira (University College London); Mikael Brudfors (King's College London); Andrew Kayser (University of California, San Francisco); Mark D'Esposito (University of California, Berkeley); Cathy Price (University College London); Ioannis Pappas (University of Southern California); John Ashburner (University College London)

Ultra-Resolution Cascaded Diffusion Model for Gigapixel Image Synthesis in Histopathology
Sarah Cechnicka (Imperial College London)*; Hadrien Reynaud (Imperial College London); James H Ball (Imperial College London); Naomi Simmonds (NHS); Catherine Horsfield (NHS); Andrew Smith (NHS, Imperial College London); Candice Roufosse (NHS, Imperial College London); Bernhard Kainz (Imperial College London, FAU Erlangen-Nürnberg)

A Recall On Thin Structures
Yannick Kirchhoff (DKFZ)*; Maximilian R Rokuss (German Cancer Research Center (DKFZ)); Saikat Roy (German Cancer Research Center (DKFZ)); Balint Kovacs (German Cancer Research Center (DKFZ) Heidelberg); Constantin Ulrich (German Cancer Research Center (DKFZ) ); Tassilo Wald (DKFZ); Maximilian Zenk (German Cancer Research Center (DKFZ)); Fabian Isensee (German Cancer Research Center (DKFZ)); Klaus H. Maier-Hein (German Cancer Research Center (DKFZ))

M3-X: Multimodal Generative Model for Screening Mammogram Reading and Explanation
Man Luo (Arizona State University)*; Amara Tariq (Mayo Clinic); Bhavik Patel (Mayo Clinic); Imon Banerjee (Mayo Clinic Arizona)

Towards Generalist Models for Multimodal Clinical Diagnostics
Yunxiang Fu (The University of Hong Kong); Hong-Yu Zhou (The University of Hong Kong); Yizhou Yu (The University of Hong Kong)*

Rethinking Knee Osteoarthritis Severity Grading: A Few Shot Self-Supervised Contrastive Learning Approach
Niamh Belton (Science Foundation Ireland Centre for Research Training in Machine Learning, University College Dublin)*; Misgina Tsighe Hagos (University College Dublin); Aonghus  Lawlor (University College Dublin); Kathleen Curran (UCD)

On the notion of Hallucinations from the lens of Bias and Validity in Synthetic CXR Images
Gauri Bhardwaj (AIShield); Yuvaraj Govindarajulu (Bosch AIShield)*; Sundaraparipurnan Narayanan (AI Tech Ethics); Pavan Kulkarni (Bosch Global Software Technologies Pvt. Ltd); Manojkumar Parmar (Robert Bosch)

Temporal Fine-tuning of Medical Vision-Language Representation
Haoxu Huang (New York University)*; Cem M Deniz (NYU Langone Health); Kyunghyun Cho (New York University); Sumit Chopra (Courant Institute of Mathematical Sciences); Divyam  Madaan (New York University)

ProsDectNet: Bridging the Gap in Prostate Cancer Detection via Transrectal B-mode Ultrasound Imaging
Sulaiman Vesal (Stanford University)*; Indrani Bhattacharya (Stanford University); Hassan Jahanandish (Stanford University); Cynthia Xinran Li (Stanford University); Moonhyung Choi  (Stanford University); Steve Ran Zhou (Stanford University); Zachary Kornberg (Stanford University); Elijah Richard  Sommer (Stanford University); Richard Fan (Stanford University); Geoffrey A Sonn (Stanford University); Mirabela Rusu (Stanford University)

Mapping and Diagnosing Augmented Whole Slide Image Datasets with Training Dynamics
Wenqi Shi (Georgia Tech)*; Benoit Marteau (Georgia Tech); Felipe Giuste (Georgia Tech); May D Wang (Georgia Institute of Technology)

Adapting Machine Learning Diagnostic Models to New Populations Using a Small Amount of Data: Results from Clinical Neuroscience
Rongguang Wang (University of Pennsylvania)*; Pratik Chaudhari (University of Pennsylvania); Christos Davatzikos (University of Pennsylvania) 

Convolve and Conquer: Data Comparison with Wiener Filter
Deborah Pelacani Cruz (Imperial College London)*; George Strong (Imperial College London); Oscar Bates (Imperial College); Carlos Cueto (Imperial College London); Jiashun Yao (Imperial College London); Lluis Guasch (Imperial College London)

Sculpting Efficiency: Pruning Medical Imaging Models for On-Device Inference
Sudarshan Sreeram (Imperial College London)*; Bernhard Kainz (Imperial College London, FAU Erlangen-Nürnberg)

CellMixer: Annotation-free Semantic Cell Segmentation of Heterogeneous Cell Populations
Mehdi Naouar (University of Freiburg)*; Gabriel Kalweit (University of Freiburg); Anusha Klett (CRIION - Collaborative Research Institute Intelligent Oncology); Yannick Vogt (University of Freiburg); paula silvestrini (CRIION - Collaborative Research Institute Intelligent Oncology); Diana Laura  Infante Ramirez (CRIION - Collaborative Research Institute Intelligent Oncology); Roland Mertelsmann (University Medical Center Freiburg); Joschka Boedecker (University of Freiburg); Maria Kalweit (University of Freiburg)

ProtoEEGNet: An Interpretable Approach for Detecting Interictal Epileptiform Discharges
Dennis Tang (Duke University)*; Frankie Willard (Duke University); Ronan C Tegerdine (Duke University ); Luke Triplett (Duke University); Jonathan C Donnelly (University of Maine); Luke Moffett (Duke University); Lesia Semenova (Duke University); Alina J Barnett (Duke University); Jin Jing (Harvard); Cynthia Rudin (Duke); Brandon Westover (Harvard University)

Universal Noise Annotation: Unveiling the Impact of Noisy annotation on Object Detection
Kwangrok Ryoo (LG AI Research)*; Yeonsik Jo (LG AI Research); Seungjun Lee (LG AI Research); Mira Kim (Korea University); Ji Ye Kim (LG AI Research); Ahra Jo (LG AI Research); Seung Hwan Kim (LG AI Research); Seungryong Kim (Korea University); Soonyoung Lee (LG AI Research)

Mitigating Spurious Correlations for Medical Image Classification via Natural Language Concepts
An Yan (UC San Diego)*; Yu Wang (University of California, San Diego); Petros K Karypis (UC San Diego); Zexue He (University of California, San Diego); Amilcare Gentili (San Diego VA & UCSD); Chun-Nan Hsu (UC San Diego); Julian McAuley (UCSD)

MRI Reconstruction with Fourier-Constrained Diffusion Bridges
Muhammad U Mirza (Bilkent)*; Onat Dalmaz (Stanford University); Hasan A Bedel (Bilkent University); Gökberk Elmas (Bilkent University); Alper Güngör (ASELSAN Research Center); Tolga Cukur (Bilkent University)

Automated Neuroimaging Pipeline to Identify Structural Biomarkers using Deep Learning Segmentation Applied to Adolescent Mental Disorders
Margot Wagner (University of California San Diego)*; Brandon Liu (University of California San Diego); Alessandra Camassa (Salk Institute); Gert Cauwenberghs (UC San Diego); Terry Sejnowski (Salk Institute for Biological Studies)

SITReg: Multi-resolution architecture for symmetric, inverse consistent, and topology preserving image registration
Joel Honkamaa (Aalto University)*; Pekka Marttinen (Aalto University)

Hierarchical Vision Transformers for Context-Aware Prostate Cancer Grading in Whole Slide Images
Clément Grisi (Radboudumc)*; Geert Litjens (Radboud Univ. Medical Ctr.); Jeroen van der Laak (Radboud University Medical Center)

A multi-modal image pipeline for automated generation of large, labeled H&E image data-sets
Matthew E Lee (University of Pennsylvania)*; Victoria Fang (University of Pennsylvania); Rami Vanguri (Children's Hospital of Philadelphia); Abigail Zellmer (Children's Hospital of Philadelphia); Amy Baxter (Children's Hospital of Philadelphia); Dokyoon Kim (University of Pennsylvania); Derek Oldridge (Children's Hospital of Philadelphia); John Wherry (University of Pennsylvania)

Thinking Outside the Box: Orthogonal Approach to Equalizing Protected Attributes
Jiahui Liu (University of Southampton)*; Xiaohao Cai (University of Southampton); Mahesan Niranjan (University of Southampton)

Assessment of Explainable AI Approaches in the Context of Digital Histopathology
Alexander Claman (University of Miami); Alicia Bilbao Martinez (University of Miami); Nicolas Echevarrieta-Catalan (University of Miami); Daniel Bilbao-Cortes (University of Miami); Vanessa Aguiar-Pulido (University of Miami)*

Performance-based Wisdom of the Crowd Algorithms for Medical Image Dataset Labeling
Eeshan Hasan (Indiana University Bloomington)*; Erik P Duhaime (Centaur Labs); Jennifer Trueblood (Indiana University Bloomington)

Enhancing Instance-Level Image Classification with Set-Level Labels
Renyu Zhang (University of Chicago)*; Aly Khan ( Toyota Technological Institute at Chicago); Yuxin Chen (UChicago); Robert Grossman (University of Chicago)

MoCo-Transfer:  Investigating out-of-distribution contrastive learning for limited-data domains
Yuwen Chen (Duke University)*; Helen Zhou (Carnegie Mellon University); Zachary  Lipton (Carnegie Mellon University)

Improved Decoding of Audio-Evoked fMRI Sequences with Sequential Transfer Learning
Sean Paulsen (Dartmouth College)*; Michael Casey (Dartmouth College)

Patient-adaptive and Learned MRI Data Undersampling Using Neighborhood Clustering
Gautam Siddhant (Michigan State University)*; Angqi Li (Michigan State University); Saiprasad Ravishankar (Michigan State University)

SAM vs BET: A Comparative Study for Brain Extraction and Segmentation of Magnetic Resonance Images using Deep Learning
Sovesh Mohapatra (University of Massachusetts Amherst)*; Advait Gosai (University of Massachusetts Amherst); Gottfried Schlaug (University of Massachusetts Amherst)

Class-Incremental Continual Learning for General Purpose Healthcare Models
Amritpal Singh (Georgia Institute of Technology )*; Mustafa B Gurbuz (Georgia Institute of Technology); Prahlad Jasti (Georgia Institute of Technology); Shiva Souhith Gantha (Georgia Institute of Technology)

Uncovering the latent dynamics of whole-brain fMRI tasks with a sequential variational autoencoder
Eloy Geenjaar (Georgia Institute of Technology)*; Donghyun Kim (Georgia Institute of Technology); Riyasat Ohib (Georgia Tech); Marlena Duda (TReNDS Center); Amrit Kashyap (Charite University Hospital); Sergey Plis (Georgia State University); Vince Calhoun (TReNDS)

Decentralized Sparse Federated Learning for Efficient Training on Distributed NeuroImaging Data
Bishal Thapaliya (Georgia State University)*; Riyasat Ohib (Georgia Tech); Eloy Geenjaar (Georgia Institute of Technology); Jingyu Liu (Georgia State University); Vince Calhoun (TReNDS); Sergey Plis (Georgia State University)

Multi-task Learning for Optical Coherence Tomography Angiography (OCTA) Vessel Segmentation
Can Koz (Oxford University); Onat Dalmaz (Stanford University)*; Mertay Dayanc (Google)

Face-GPS: A Comprehensive Technique for Quantifying Facial Muscle Dynamics in Videos
Juni C Kim (Stanford Online High School)*; Zhikang Dong (Stony Brook University); Pawel Polak (Stony Brook University)

Calibrating Where It Matters: Constrained Temperature Scaling
Stephen J. McKenna (University of Dundee)*; Jacob Carse (University of Dundee)

MIMIC-NLE-v2: Can Large Language Models Reason about Chest X-rays?
Maxime Kayser (University of Oxford)*; Oana-Maria Camburu (University College London); Thomas Lukasiewicz (Vienna University of Technology)

Zero-Shot Image Registration through Feature Extraction (ZSIR - FE): Medical Image Registration using Pre-Trained Neural Networks
Abjasree S (IIT Madras )*; Avinash Kori (ICL); Ganapathy Krishnamurthi (IIT-Madras)

Semi-Supervised Diffusion Model for Brain Age Prediction
Ayodeji Ijishakin (University College London)*; Sophie A Martin (University College London); florence townend (university college london); Federica Agosta (San Raffaele Scientific Institute); James Cole (University College London); Andrea Malaspina (University College London)

Overcoming Challenges of Small Data and Over-parameterized DNN in fMRI-based Diagnosis
Kimia Alavi (University of Tehran ); Saeed Masoudnia (School of Cognitive Sciences, Institute for research in fundamental sciences (IPM))*; Ahmad Kalhor (University of Tehran); Mohammadreza Nazemzadeh (Monash University)

Multi-Task Learning for Segmentation of Breast Arterial Calcifications in Mammograms
Aisha Urooj (Mayo Clinic Arizona)*; William Charles O'Neill (Emory University); Hari Trivedi (Emory University); Imon Banerjee (Mayo Clinic Arizona)

Dual-Channel Reliable Breast Ultrasound Image Classification Based on Explainable Attribution and Uncertainty Quantification
Shuge Lei (University of South Carolina)*