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Instructor

Dr. Moti Freiman

Reception Hours: Monday:
16:30 pm — 17:30 pm
prearrange via email
*To set up meeting see below

Teaching Assistant

Samah Khawaled

Reception Hours: Tuesday:
12:30 pm — 1:30 pm
prearrange via email
*To set up meeting see below

*How to Prearrange Reception Hours: Email either Dr. Moti Freiman or Samah Khawaled. The subject MUST be:
Impr: <Your Subject>;
where <Your Subject> is the topic you would like to discuss

About the Course

Deep-learning is now the state-of-the-art machine learning model across a variety of areas. These developments have a huge potential for Magnetic Resonance Imaging (MRI) technology. This course provides an overview of recent advances in deep-learning applied to MRI image analyis.

The course starts with a brief introduction to the theoretical and practical aspects of deep-learning. We then delve into understanding how deep-learning has been applied to the entire MRI processing chain including acquisition, reconstruction, restoration, registration, segmentation, and diagnosis.

Details

Course Title: Deep Learning Applications in MRI

Course Ref. Num. 336028

Num. or Credits: 2

Course Time: Lecture - 10:30-12:30; WEDNESDAY

Course Location: Silver Building, Room 202

Learning Objectives

Students acquire the ability to:

formulate a challenge in a MRI processing pipeline by a neural network.
implement a deep-neural-network to solve a given challenge such as:

- Segmentation

- Registration

- Reconstruction/Restoration

- Disease prediction

- Quantitative MRI analysis (specifically, Diffusion-Weighted MRI)
train and evaluate a deep-neural network.

Course site

Technion Institute of Technology
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Faculty of Biomedical Engineering
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