Image Processing

Original papers are invited on all aspects of the processing and analysis of medical, small animal, or cellular images, with applications in medicine, biological, and pharmaceutical research. Of interest are algorithms applied to all imaging modalities, including x-ray, DSA, CT, MRI, neuroimaging, nuclear medicine, optical, ultrasound, macroscopic, and microscopic imaging. Papers dealing with the challenges of bringing advances in research laboratories into clinical application are particularly welcomed.

Papers typically involve research that includes one or more of the following categories:

• augmented/virtual reality
• classification
• compressed sensing, sparse reconstruction methods
• computational anatomy and atlases
• computer vision
• connectome analysis
• deep learning
• deformable geometry
• diffusion MRI analysis
• functional imaging analysis
• generative/adversarial learning
• image representation and compression
• image restoration and enhancement
• image synthesis
• imaging genetics
• machine learning and pattern recognition
• methods for training and validation, including ground truth generation
• model-based image analysis
• motion/time series analysis
• open software for medical image processing
• population/clinical studies
• quantitative image analysis/quantitative imaging biomarkers
• registration methodologies
• radiomics and texture representation/analysis
• segmentation methodologies
• shape representation and analysis
• statistical methodology
• visualization methods
• voxel/deformation/tensor-based morphometry.

Deep-Dive Session
A limited number of papers selected for oral presentation will be chosen for a novel deep-dive session. This session will comprise very few oral presentations followed by a longer more in-depth discussion that will be led by experienced researchers. In order to be considered for the deep-dive session, select it as one of your topics in the topics selection step of the abstract submission process (it is the first-listed topic).