Scope and Objectives

The development of computational algorithms for the analysis of anatomical/structural medical images depicting only a snapshot of the living tissue has been the primary focus of past MICCAI proceedings and workshops. Medical imaging modalities that capture changes in living tissue with time are becoming more prevalent and provide a valuable source of knowledge about tissue and organ processes and physiology. This workshop provides a venue for presenting the latest advances in mathematical techniques and computational algorithms for extracting clinically relevant information from functional and time-varying medical image data.


Contributions are solicited in, but are not limited to, the following areas:

  • Novel algorithms for processing and analysis of functional medical image data, including denoising, enhancement, restoration, clustering, segmentation, tracking, matching, registration, fusion, and kinetic modeling.

  • Methods for information extraction from functional medical image modalities including positron emission tomography (PET), single photon emission computed tomography (SPECT), functional magnetic resonance imaging (fMRI), dynamic contrast-enhanced MRI (DCE MRI), tagged MRI, phase contrast MRI, flow imaging, ultrasound, and from multi-modal data fused with other signals such as MEG or EEG.

  • Functional medical image computing algorithms (computational physiology) for quantification and analysis of electro-physiological signals, motion patterns, tracer uptake and tissue kinetics, perfusion, flow, activation patterns, responses to stimuli, progress of pathology or treatments, and other processes related to cardiac, neural, musculoskeletal, renal, blood and other organs, tissues, and fluids at a variety of scales of molecular, cellular, tissue, organ, and whole body imaging.