SUNRISE EDUCATIONAL COURSE
Computer-Aided Diagnosis: Managing the Information Explosion
ORGANIZER: Pratik Mukherjee, M.D., Ph.D.
 
SKILL LEVEL: Appropriate for all skill levels
 

OVERVIEW
The topics to be covered in this four-hour course are related to the emerging technologies of machine learning and computer-aided diagnosis, including their application to MRI datasets, as well as new trends in imaging informatics. Our overall goal is to help educate MR scientists, Ph.D. students and clinicians to exciting new developments in "quantitative imaging", including automated post-processing, data-driven feature extraction, and computer-aided lesion detection, as applied to neuro MRI and body MRI. New informatics technologies including cloud computing will also be covered. Speakers are mainly Ph.D. scientists and M.D.-Ph.D. clinician-scientists with expertise in computer science and/or information technology. The format will be lectures, each followed by a brief discussion period.
 
EDUCATIONAL OBJECTIVES
Upon completion of this course participants should be able to:
Describe new trends in analyzing large and complex imaging datasets, especially as related to MRI;
Explain the basic concepts of machine learning and multivariate statistics, especially as applied to medical imaging;
Describe the potential applications and possible pitfalls of supervised and unsupervised machine learning methods;
Evaluate potential applicability of machine learning and computer-aided detection to neuro MRI, body MRI, and MSK MRI; and
Recommend implementing particular emerging machine learning and/or computer-aided diagnosis techniques at their institution.
 
AUDIENCE DESCRIPTION
The intended audience includes the entire ISMRM community, including Ph.D. MR scientists and engineers, M.D. clinicians as well as all trainees including students and postdocs.

PROGRAM

Click on to view the abstract pdf. Click on to view the recorded presentation.

  Tuesday, 8 May 2012
Moderators: Joseph A. Maldjian, M.D. & Pratik Mukherjee, M.D., Ph.D.
     
07:00 Data-Driven Feature Extraction from Complex MRI Datasets: PCA, ICA, Etc. Stephen M. Smith, D.Phil.
07:30 Machine Learning Classification & Regression Edward H. Herskovits, M.D., Ph.D.
     
08:00 Adjournment  
     
  Wednesday, 9 May 2012
Moderators: Joseph A. Maldjian, M.D. & Pratik Mukherjee, M.D., Ph.D.
     
07:00 Machine Learning in Neuroradiology I Joseph A. Maldjian, M.D.
07:30 Machine Learning in Neuroradiology II  Edward H. Herskovits, M.D., Ph.D.
     
08:00 Adjournment  
     
  Thursday, 10 May 2012
Moderators: Joseph A. Maldjian, M.D. & Pratik Mukherjee, M.D., Ph.D.
     
07:00 CAD of Breast MRI Savannah C. Partridge, Ph.D.
07:30 CAD of Liver MRI Jeffrey H. Maki, M.D., Ph.D.
     
08:00 Adjournment  
     
  Friday, 11 May 2012
Moderators: Joseph A. Maldjian, M.D. & Pratik Mukherjee, M.D., Ph.D.
     
07:00 CAD of Musculoskeletal MRI: Automated Morphometric Analysis Julio Carballido-Gamio, Ph.D.
07:30 CAD of Musculoskeletal MRI: Feature Detection using T2 & T1rho Relaxometry Julio Carballido-Gamio, Ph.D.
     
08:00 Adjournment