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ORCIDLDTM/MMMI/ML4MHD/ML-CDS@MICCAI 2024: Marrakesh, Morocco
- Anna Schroder, Xiang Li
, Tanveer F. Syeda-Mahmood, Neil P. Oxtoby, Alexandra L. Young, Alessa Hering, Tejas Sudharshan Mathai, Pritam Mukherjee, Sven Kuckertz, Tiantian He, Isaac Llorente-Saguer, Andreas Maier, Satyananda Kashyap, Hayit Greenspan, Anant Madabhushi:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 Workshops - LDTM 2024, MMMI/ML4MHD 2024, ML-CDS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6-10, 2024, Proceedings. Lecture Notes in Computer Science 15401, Springer 2025, ISBN 978-3-031-84524-6
LDTM Workshop
- Alessandro Viani, Boris A. Gutman, Emile d'Angremont, Marco Lorenzi:
Disease Progression Modelling and Stratification for Detecting Sub-trajectories in the Natural History of Pathologies: Application to Parkinson's Disease Trajectory Modelling. 3-14 - Nico Disch, Robin Peretzke, Saikat Roy, Constantin Ulrich, David Zimmerer, Rainer Stiefelhagen, Jens Kleesiek, Klaus H. Maier-Hein:
Back to the Future: Challenges of Sparse and Irregular Medical Image Time Series. 15-25 - Rosemary He, Gabriella Ang, Daniel Tward:
Individualized Multi-horizon MRI Trajectory Prediction for Alzheimer's Disease. 26-37 - Pedro M. Gordaliza, Nataliia Molchanova, Maxence Wynen, Pietro Maggi, Alessandro Cagol, Cristina Granziera, Meritxell Bach Cuadra:
Towards Longitudinal Characterization of Multiple Sclerosis Atrophy Employing SynthSeg Framework and Normative Modeling. 38-51 - Berke Doga Basaran, Xinru Zhang, Paul M. Matthews, Wenjia Bai:
SegHeD: Segmentation of Heterogeneous Data for Multiple Sclerosis Lesions with Anatomical Constraints. 52-63 - Maximilian Rokuss, Yannick Kirchhoff, Saikat Roy, Balint Kovacs, Constantin Ulrich, Tassilo Wald, Maximilian Zenk, Stefan Denner, Fabian Isensee, Philipp Vollmuth, Jens Kleesiek, Klaus H. Maier-Hein:
Longitudinal Segmentation of MS Lesions via Temporal Difference Weighting. 64-74 - Walid Yassine, Martin Charachon, Céline Hudelot, Roberto Ardon:
Registration of Longitudinal Liver Examinations for Tumor Progress Assessment. 75-87 - Prateek Mathur, Brendan S. Kelly, Ronan P. Killeen, Aonghus Lawlor:
Tracking Lesion Evolution Using a Boundary Enhanced Approach for MS Change Segmentation (BEAMS). 88-100 - Teresa M. T. Bucho, Thierry N. Boellaard, Mateus Taveira, Zuhir Bodalal, Thi D. L. Nguyen-Kim, Regina Beets-Tan, Stefano Trebeschi:
A Radiological-Based Coordinate System for the Human Body: A Proof-of-Concept. 101-110
MMMI-ML4MHD Workshop
- Jun Li, Su Hwan Kim, Philip Müller, Lina Felsner, Daniel Rueckert, Benedikt Wiestler, Julia A. Schnabel, Cosmin I. Bercea:
Language Models Meet Anomaly Detection for Better Interpretability and Generalizability. 113-123 - Zizhen Ji, Rui Chen, Pinyu Qiu, Xiaoyong Fu, Sheng Li, Jun Tan:
A Diffusion Model Embedded WCSAU-Net for 3D MRI Brain Tumor Segmentation. 124-135 - Yifei Sun, Mariano Cabezas, Jiah Lee, Chenyu Wang, Wei Zhang, Fernando Calamante, Jinglei Lv:
Predicting Human Brain States with Transformer. 136-146 - Annette Schwarz, Jannis Dickmann, Christian Hofmann, Juliane Szkitsak, Christoph Bert, Andreas Maier, Tomás Arias-Vergara:
Cross-Modality Image Quality Prediction for Time-Resolved CT from Breathing Signals. 147-156 - Anqi Feng, Zhangxing Bian, Blake E. Dewey, Alexa Gail Colinco, Jiachen Zhuo, Jerry L. Prince:
RATNUS: Rapid, Automatic Thalamic Nuclei Segmentation Using Multimodal MRI Inputs. 157-169 - Hava Chaptoukaev, Vincenzo Marcianó, Francesco Galati, Maria A. Zuluaga:
HyperMM: Robust Multimodal Learning with Varying-Sized Inputs. 170-183 - Chang Bian, Beth Phillips, Tim Cootes, Martin Fergie:
HEMIT: H&E to Multiplex-Immunohistochemistry Image Translation with Dual-Branch Pix2pix Generator. 184-197 - Sven Lüpke, Yousef Yeganeh, Ehsan Adeli, Nassir Navab, Azade Farshad:
Physics-Informed Latent Diffusion for Multimodal Brain MRI Synthesis. 198-207
ML-CDS Workshop
- Mai A. Shaaban, Adnan Khan, Mohammad Yaqub:
MedPromptX: Grounded Multimodal Prompting for Chest X-Ray Diagnosis. 211-222 - Yuqing Huang, Bastian Wittmann, Olga V. Demler, Bjoern H. Menze, Neda Davoudi:
Predicting Stroke Through Retinal Graphs and Multimodal Self-supervised Learning. 223-234 - DaeHyun Cho, Young Ho Kim, Somin Ahn, Jaeryung Oh, Christian Wallraven:
Multimodality for Diagnosis of Asian Choroidal Vasculopathy: Results from a Novel Dataset and Deep-Learning Experiments. 235-247 - Feifei Jin, Cheng Zhao, Peng Yang, Zhuo Xiang, Xunyi Chen, Yu Zhang, Shumin Fan, Luyao Zhou, Weiling Chen, Tianfu Wang, Baiying Lei:
Multimodality Frequency Feature Customized Learning for Pediatric Ventricular Septal Defects Identification. 248-259
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