Reconstruction and Analysis of Moving Body Organs (RAMBO) 2017

The 2nd international workshop on Reconstruction and Analysis of Moving Body Organs was held in conjunction with the 20th International Conference on Medical Image Computing and Computer Assisted Intervention 2017 in Quebec, Canada on 10 September 2017.

This workshop targets researchers for whom the effects of motion are critical in image analysis or visualisation. By inviting contributions across all application areas we aim to bring together ideas from different fields without being confined to a particular methodology. In particular, the move from model-based to learning-based methods of modelling over recent years has resulted in increased transferability of techniques between domains. RAMBO provides a forum for the dissemination and discussion of novel developments related to dealing with, and taking advantage of, motion in medical imaging.

Workshop date: 10 September 2017, 1:30PM - 5:35PM

Location: 302A

The workshop was again a great success. Workshop proceedings can be downloaded from Springer LNCS 10555.


Keynote talks

Dr Aleksandra Popovic: Department Head, Philips Research North America

Keynote talk: From anatomy reconstruction to autonomous surgical robots



Dr. Ali Gholipour: Professor in Radiology, Harvard Medical School

Keynote talk: Imaging technology for fetal brain connectivity analysis


We invite submissions on any aspect of medical imaging where motion plays a role in the image formation or analysis. Topics include, but are not limited to:

  • Cardiac, respiratory, fetal, colon, fMRI, interventional applications
  • Motion modelling (including methods to learn motion)
  • Time series analysis
  • Image registration
  • Image segmentation / classification
  • Real-time applications
  • Machine learning methods
  • Image reconstruction
  • Image enhancement (e.g. super-resolution, denoising)
  • Compressed sensing / accelerated imaging

This year, RAMBO will additionally host CoronARe: A Coronary Artery Reconstruction Challenge.