Machine Learning for Medical Imaging

The overall purpose of the ML4MI initiative is to foster interdisciplinary collaboration between machine learning (ML) experts and medical imaging researchers at the University of Wisconsin, in order to develop and apply state-of-the-art ML solutions to challenging problems in medical imaging. This initiative responds to rapidly growing interest in ML techniques within medical imaging research, due to the unprecedented potential to solve challenging problems in areas such as image reconstruction, image processing, and computer-aided diagnosis. ML4MI is generously supported by the UW Departments of Radiology and Medical Physics, and the Grainger Institute for Engineering.

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Monthly seminars

A regular seminar series began in February 2018, and includes 1) seminars describing technical developments in ML with potential biomedical applications, 2) seminars by local or external Radiology researchers, describing problems that may benefit from ML approaches and ongoing projects involving ML techniques, and 3) seminars by biomedical researchers (not in Radiology), describing pioneering experiences applying ML in their fields of study. The seminar location will alternate between ECB/WID and SMPH/WIMR. These seminars will also provide an opportunity for UW researchers to become familiar with researchers “on the other side of campus.”

Pilot grant proposals – 2019 RFA now open

The purpose of this pilot grant program is to foster interdisciplinary collaboration between ML experts and medical imaging clinicians and researchers at the University of Wisconsin’s Departments of Radiology and Medical Physics, and College of Engineering. Specific topics of interest include the development and characterization of novel ML methods with significant medical imaging applications, and the development and validation of new imaging applications for state-of-the-art ML methods.

In 2018, pilot grants were awarded to the following collaborative teams:

– Kevin Johnson,  Alejandro Roldan, and Shiva Rudraraju, “Patient specific hemodynamics using machine learning based fusion of MRI measurements and computational fluid dynamics”

– Varun Jog and Alan McMillan, “DeepRad: An accessible, open-source tool for deep learning in medical imaging”

2019  ML4MI Summer Bootcamp

Building on last year’s experience, we will be hosting an ML4MI bootcamp in August 2019. This is a repeat of the bootcamp held last summer and has the goal of giving participants a rapid, hands-on introduction into the principles and application of machine learning for medical imaging. This bootcamp is supported by the Grainger Institute of Engineering and the Departments of Radiology and Medical Physics.

When:  August 22-23, 9am-1pm OR August 22-23, 1pm-5pm
Where: WIMR 1022
Registration (required): https://forms.gle/3NKpi8E3VdTnY1gq5

Please feel free to contact the organizers with questions:

Kevin Johnson (kmjohnson3@wisc.edu)
Alan McMillan (AMcmillan@uwhealth.org)
Tyler Bradshaw (tbradshaw@wisc.edu)

PREVIOUS WORKSHOP: OCTOBER 5, 2018 

This workshop was held on October 5, 2018 at the UW Fluno Center. The one-day workshop featured keynote talks by leaders in the fields of ML and Radiology, a seminar on bioethics, a panel of radiologists, and poster presentations by junior researchers.

Workshop Agenda

Contact:

• Diego Hernando, PhD (Radiology and Medical Physics, email: dhernando@wisc.edu)
• Varun Jog, PhD (Electrical and Computer Engineering, email: vjog@wisc.edu)
• Kevin Johnson (Medical Physics and Radiology, email: kmjohnson3@wisc.edu)
• Po-Ling Loh, PhD (Electrical and Computer Engineering, email: loh@ece.wisc.edu)
• Alan McMillan (Radiology, email: AMcmillan@uwhealth.org)