CS-8395 Deep Learning in Medical Image Computing

* Important Notice. We will have both office hour and class through ZOOM (Same Time as Scheduled)

Classroom: https://vanderbilt.zoom.us/j/613153831

TA Office hour: https://vanderbilt.zoom.us/s/779998946

Faculty Office hour: https://vanderbilt.zoom.us/j/613153831

I. Course Information:

Deep Learning is prevalent since 2015 in medical image computing. This class covers the theories and practices of Deep Learning related to medical image computing.

II. Teaching Team:
Instructor:                  Yuankai Huo     Email: yuankai.huo@vanderbilt.edu
Teaching Assistant:  Roza Bayrak     Email: roza.g.bayrak@vanderbilt.edu

Class Meets: Tuesday & Thursday, 4:00 pm – 5:15 pm, FGH 110
TA Office Hours: Tuesday & Thursday, 1:00 pm – 4:00 pm, TA Office (FGH 385 or 375)
Instructor Office Hours: Tuesday & Thursday, 3:00 pm – 4:00 pm, (FGH 376)

Course Website: https://my.vanderbilt.edu/cs8395
Submission & Discussion: https://www.vanderbilt.edu/brightspace

III. Schedule




Jan 07 Overview of Deep Learning in Medical Image Computing slides
Jan 09 Neural Networks and CNN slides, reading1
Jan 14 Classification (Medical Image Diagnosis) slides, reading2
Jan 16 Detection (Landmark Localization and Detection) slides, reading3
Jan 21 Segmentation (Medical Image Segmentation) slides, reading4
Jan 23 GAN (Medical Image Synthesis) slides, reading5
Jan 28 Assignment 1 Presentation
Jan 30 Multi-modal Learning slides, reading6
Feb 04 Multi-task Learning slides, reading7
Feb 06 Beyond 2D: 3D Networks slides, reading8
Feb 11 Semi-/weakly-supervised Learning slides, reading9
Feb 13 Assignment 2 Presentation
Feb 18 Unsupervised Learning slides, reading10
Feb 20 Data Augmentation and Preprocessing slides, reading11
Feb 25 Final Project Proposal example
Feb 27 Final Project Proposal
Mar 03 No Class: Spring Break!
Mar 05 No Class: Spring Break!
Mar 10 No Class: COVID-19
Mar 12 No Class: COVID-19
Mar 17 Attention Mechanism and Postprocessing slides, reading12
Mar 19 Spatial-temporal Model: RNN and LSTM slides, reading13
Mar 24 Assignment 3 Presentation
Mar 26 Image Retrieval and Active Learning slides, reading14
Mar 31 Image Text Co-learning slidesreading15
Apr 02 Learn from Prior and Online Learning slides, reading16
Apr 07 Summary
Apr 09 Final Project Presentation
Apr 14 Final Project Presentation
Apr 16 Final Project Presentation

IV. Assignments



Due Date

Reading Assignments Template Begining of the class
Assignment 0: Eligibility Test PDF Jan 09 2020, 4:00 pm
Assignment 1: Detection PDF Jan 28 2020, 9:00 am
Assignment 2: Classification PDF Feb 13 2020, 9:00 am
Assignment 3: Segmentation PDF Mar 26 2020, 9:00 am
Final Project Example Apr 20 2020, 9:00 am

* Teamwork is not allowed for assignments.

V. Assignments, Mid Term Exam, and Final Project

More details are provided Here.

VI. Computational Resource

GPU computing is required for this class. I strongly recommend to use your own/lab’s GPU since that is the most convenient way of writing and testing code with GUI. However, if you don’t have any GPU computational resource, you can use the GPU on ACCRE by filling the following two forms:
1. ACCRE registration form
2. GPU requirement form
If you are already using ACCRE, you can submit a helpdesk ticket instead to request access to your class group. There is a relatively large demand for GPU resources at ACCRE, so limited GPU resources will be provided for this class.
*The deadline of ACCRE resource application is the due date of assignment 1.


1. The class is full. Can I still get in?
It is unlikely except other students drop it during the first week.
2. What is pre-requirement?
Linear algebra, programming in python, introduction in machine learning.
3. Can I sit in class without registering?
Yes after getting the instructor’s approval. Another option is to register to audit the class (just $50).

VIII. References

* We used images and contents in the slides from the following resources, thanks for the great work done by the smart people!