Following the 26th International Conference on Medical Image Computing and Computer Assisted Intervention main conference, we will host the Multiscale Multimodal Medical Imaging Workshop on Oct 8, 2023. The purpose of this workshop is to 1) techniques involving multi-modal image acquisition and reconstruction, or imaging at multi-scales; 2) novel methodologies and insights of multiscale multimodal medical images analysis, including image fusing, multimodal augmentation, and joint inference; and 3) empirical studies involving the application of multiscale multimodal imaging for clinical use. We also strongly encourage workshops aiming to create and strengthen communities. To this end, we are soliciting paper submissions and looking forward your coming for this workshop.

Overview

Facing the growing amount of data available from multiscale multimodal medical imaging facilities and a variety of new methods for the image analysis developed so far, this MICCAI workshop aims to move the forward state of the art in multiscale multimodal medical imaging, including both algorithm development, implementation of the methodology, and experimental studies. The workshop also aims to facilitate more communications and interactions between researchers in the field of medical image analysis and the field of machine learning, especially with expertise in data fusion, multi-fidelity methods, and multi-source learning.

Scope and Topics

Interested topics will include, but not be limited to:

• Image segmentation techniques based on multiscale multimodal images
• Novel techniques in multiscale multimodal image acquisition and reconstruction
• Registration methods across multiscale multimodal images
• Fusion of images from multiple resolutions and novel visualization methods
• Spatial-temporal analysis using multiple modalities
• Fusion of image sources with different fidelities: e.g., co-analysis of EEG and fMRI
• Multiscale multimodal disease diagnosis/prognosis using supervised or unsupervised methods
• Atlas-based methods on multiple imaging modalities
• Cross-modality image generative methods: e.g., generation of synthetic CT/MR images
• Novel radiomics methods based on multiscale multimodal imaging
• Shape analysis on images from multiple sources and/or multiple resolutions
• Graph methods in medical image analysis
• Benchmark studies for multiscale multimodal image analysis: e.g., using electrophysiological signals to validate fMRI data
• Multi-view machine learning for cancer diagnosis and prognosis
• Integrated radiology, pathology, and genomics analysis via learning algorithms
• New image biomarker identification through multiscale multimodal data
• Integrated learning using both image and non-image data

Important Dates

Paper Submission Deadline: July 14th, 2023

Decision Notification Date: July 28th, 2023

Camera-ready Deadline: August 4th, 2023

Workshop Date: Oct 8th, 2023