Description
Book SynopsisLDTM Workshop.- Disease Progression Modelling and Stratification for detecting sub-trajectories in the natural history of pathologies: application toParkinson's Disease trajectory modelling.- Back to the Future: Challenges of Sparse and Irregular Medical Image Time Series.- Individualized multi-horizon MRI trajectory prediction for Alzheimer's Disease.- Toward, for the Alzheimer's Disease Neuroimaging Initiative Towards Longitudinal Characterization of Multiple Sclerosis Atrophy Employing SynthSeg Framework and Normative Modeling.- BachCuadraSegHeD: Segmentation of Heterogeneous Data for Multiple SclerosisLesions with Anatomical Constraints.- Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting .- Registration of Longitudinal Liver Examinations for Tumor ProgressAssessment.- Tracking lesion evolution using a Boundary Enhanced Approach for MS change segmentation (BEAMS).- A Radiological-based Coordinate System for the Human Body: A Proof-of-Concept.- MMMI-ML4MHD Workshop.- Language Models Meet Anomaly Detection for Better Interpretabilityand Generalizability.- A Diffusion Model Embedded WCSAU-Net for 3D MRI Brain Tumor Segmentation.- Predicting Human Brain States with Transformer .- Modality Image Quality Prediction for Time-Resolved CT fromBreathing Signals.- RATNUS: Rapid, Automatic Thalamic Nuclei Segmentation using Multimodal MRI inputs.- HyperMM : Robust Multimodal Learning with Varying-sized Inputs.- EMIT: H&E to Multiplex-immunohistochemistry Image Translation with Dual-Branch Pix2pix Generator.- Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis.- ML-CDS Workshop.- MedPromptX: Grounded Multimodal Prompting for Chest X-rayDiagnosis.- Predicting Stroke through Retinal Graphs and Multimodal Self-supervised Learning.- Multimodality for Diagnosis of Asian Choroidal Vasculopathy: Resultsfrom a Novel Dataset and Deep-learning Experiments.- Multimodality Frequency Feature Customized Learning for PediatricVentricular Septal Defects Identification.
