Teaching Activities at Johns Hopkins University
CS.600.661 Computer Vision (Invited Lecturer)
11/12/2018: Introduction to Deep Learning (Hodson 210, 4:30-5:45 pm) [Lecture Feedback]
11/14/2018: Introduction to Adversarial Models in Deep Learning (Hodson 210, 4:30-5:45 pm) [Lectrure Feedback]
EN.580.142.13 Deep Learning for Medical Image Analysis
2 Credits (Intersession 2019)
Days: 1/7/2019 – 1/25/2019 Instructor: Dr. Faisal Mahmood
Tues: 9am-1230pm Wed: 9am-1230pm Fri: 9am-1230pm (10 hours/week)
Office Hours: Tues: 2-5pm – Clark 100, please email email@example.com for urgent inquires.
This course will focus on teaching the theoretical and practical foundations of detection, segmentation, and classification using deep learning for medical image analysis and understanding. The course will also focus on the applications of image-to-image translation using conditional generative adversarial networks (GANs) for medical imaging problems. This will be a hands-on course with coding assignments and prior knowledge of python and fundamental calculus is recommended.
Slides / Lecture Notes / Lecture Videos / Assignments will be posted here after each lecture.
Enrollment is limited to 50 students on a first come first serve basis, please register in SIS, preference will be given to graduate students.
Week 1: Introduction to Machine Learning and Deep Learning
8/1/2019: Lecture 1: Basic Calculus and Machine Learning Review
9/1/2019: Lecture 2: Introduction to Deep Learning I (Backprop, Perceptrons, and MLPs )
11/1/2019: Lecture 3: Introduction to Deep Learning II (Convolutional Neural Networks)
Week 2: Detection, Segmentation and Classification Problems in Medical Image Analysis
15/1/2019: Lecture 4: Deep Learning Architectures for Detection and Localization (Assignment: Polyp Detection and Localization in Endoscopy)
16/1/2019: Lecture 5: Deep Learning Architectures for Classification (Assignment: Classification of Breast Cancer Lymph Node patch data)
18/1/2019: Lecture 6: Deep Learning-based Regression for Medical Imaging (Assignment: Nuclei Segmentation in H&E images)
Week 3: Advanced Topics in Deep Learning
22/1/2019: Lecture 7: Multimodal Deep Learning for Medical Imaging (Assignment: Combine Radiology and H&E data for improved classification)
23/1/2019 Lecture 8: Synthetic Medical Data Generation (Assignment: Generate Synthetic H&E image patches)
25/1/2019 Lecture 9: Interpreting Deep Models using Gradient Class Activation Maps
25/1/2019 Class Dinner (TBA)