Graduate School of Medical Sciences
A partnership with the Sloan Kettering Institute

Machine Learning with Images

Credits: 3.0
Course Directors: Joseph O. Deasy PhD, Harini Veeraraghavan PhD, Saad Nadeem PhD


Course Description

Machine learning techniques have had a huge impact on biomedical imaging over the past few years and account for a large fraction of new research. This course covers the fundamentals of machine learning and data analysis methods for analyzing medical images, focusing on radiological images, with a lesser emphasis on surgical and histopathological images.


Course Objectives

Machine learning techniques have had a huge impact on biomedical imaging over the past few years and account for a large fraction of new research. The course aims to:
1. Introduce students to applications of machine learning in biomedical imaging
2. Teach students state-of-the-art methods for data modeling using machine learning, including
a. data reduction
b. image feature extraction
c. image segmentation
d. radiomics
e. deep learning
f. transport distance methods.

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Weill Cornell Medicine Graduate School of Medical Sciences 1300 York Ave. Box 65 New York, NY 10065 Phone: (212) 746-6565 Fax: (212) 746-5981