MNT Image processing Lectures

The final lecture notes will be published the evening before each lecture.

Lecture 1: November 18th - Ground Truth and Datasets (Lecturer: Kevin Mader)

Lecture notes

• Slides
• Handout

Exercises

• Sign up for a Kaggle Account (https://www.kaggle.com/)
• A few students can use the test account

username: rsna2017
password: rsna2017

• Read about how kernels work: https://www.kaggle.com/docs/kernels

• Dataset on Kaggle https://www.kaggle.com/c/pneumonia-texture-analysis

• More background slides about the medical datasets: http://bit.ly/deeptexture

Lecture 2: December 2nd - Image and Filters

Lecture notes

1. Introduction
2. Images
3. Filters

Demo notebooks

1. Limitation of convolution
2. Details of the non-local meanse

Assignments

• Assignment 1: Images and python
• Assignment 2: Filters

Solutions

1. Solutions to assignment 1
2. Solutions to assignment 2

Lecture 3: December 9th - Classification and Morphology

Lecture notes

1. Segmentation
2. Morphology 1
3. Morphology 2

Demo notebooks

Assignments

• Assignment 3: Segmentation
• Assignment 4: Morphology

Solutions

1. Solutions to assignment 3
2. Solutions to assignment 4

Lecture 4: December 16th - Measurements and analysis strategies

Lecture notes

1. Measurements
2. Analysis strategies

Demo notebooks

1. Distance guided average

Assignments

• Final assignment: All at once

Solutions

• Solution to final assignment