Course syllabus

This page contains the program of the course: lectures and computer labs. Other information, such as learning outcomes, teachers, literature and examination, are in a separate course PM.

Program

The schedule of the course is in TimeEdit.

The course has two lectures and two computer exercises each week. Details for these are given in the schedule below, which will be updated during the course. For the lectures, the chapters covered in the books are listed, where LN denotes the lecture notes by Mats Rudemo, HS denotes the Handbook of spatial statistics and EL The Elements of Statistical Learning. 

The lectures will be given in Euler but it is also possible to follow them on Zoom using the link  https://chalmers.zoom.us/j/61569881002, Password: 642830

Projects and examination

The deadlines for the projects can be found in the end of this page under Course summary. The reports should be uploaded in Canvas/Assignments.  

In addition to the projects, there will be a final exam on June 1 at 14:00-18:00.

Lectures and Exercises

Teachers of the course are Aila Särkkä (lectures, examiner), aila@chalmers.se, and Konstantinos Konstantinou (lectures, computer exercises), konkons@chalmers.se. Lecture notes of the lectures can be found in Files/Lecture notes. The information below  will be updated and extended on an ongoing basis.

 

Time Room Lecture Computer exercise
March 21 Monday
8:00-9:45
Euler L1

Introduction, lecture notes and LN pages 1-24, see also pages 1-8 of Glasbey and Horgan 1995, Chapter 5.

 
  Monday
13:15-15:00
MVF24 and MVF25 E1  

Basic image processing

Solution

March 23  Wednesday
10:00-11:45
Euler L2 Spatial random processes, lecture notes and LN pages 69-78.  
  Wednesday
13:15-15:00
MVF24 and MVF25 E2  

Gaussian fields

Solution

March 28  Monday
8:00-9:45
Euler L3

OLS, GLS and ML estimation, lecture notes and LN pages 78-85.

 
  Monday
13:15-15:00
MVF24 and MVF25 E3  

Estimation and kriging

Solution

March 30 Wednesday
10:00-11:45
Euler L4

GMRFs, HS pages 172-175, 201-207.

LDA, QDA, image moments,  LN pages 31-38 and EL 4.3

lecture notes

 
  Wednesday
13:15-15:00
MVF24 and MVF25 E4   Continue working on exercise 3
April 4 Monday
8:00-9:45
Euler L5

Cross validation, supervised methods, LN pages 38-42 and 53-59 and sections 2.3.2, 7.10, 12.2-12.3.2, 11.3-11.5 in EL

lecture notes

 
  Monday
13:15-15:00
MVF24 and MVF25 E5  

Image reconstruction using GMRFs

Solution

April 6 Wednesday
10:00-11:45
Euler L6

Image segmentation, morphological operations and feature extraction. LN 1.5-1.6, 2.8. See also EL 8.5.1, 14.3.6-14.3.7.

lecture notes.

 
  Wednesday
13:15-15:00
MVF24 and MVF25 E6  

Image classification

Solution

April 25  Monday
8:00-9:45
Euler L7 Markov random fields, lecture notes and LN pages 60-67  
  Monday
13:15-15:00
MVF24 and MVF25 E7  

Image segmentation using mixture models

Solution

April 27 Wednesday
10:00-11:45
Euler L8 Point process analysis, lecture notes LN pages 86-93.  
  Wednesday
13:15-15:00
MVF24 and MVF25 E8  

Simulation of MRFs

Solution

May 2  Monday
8:00-9:45
Euler L9

Marked point processes, point processes with noise, lecture notes and LN pages 94-96 and 117-129.

 
  Monday
13:15-15:00
MVF24 and MVF25 E9  

Estimation and classification using MRFs

Solution

May 4  Wednesday
10:00-11:45
Euler L10 Applications of point processes/image analysis to nerve fiber data, lecture notes 
 
  Wednesday
13:15-15:00
MVF24 and MVF25 E10   Point processes
May 9  Monday
8:00-9:45
Euler L11 Guest lecture on analysing microscopy (FIB-SEM, FRAP, and particle tracking) data by Magnus Röding, RISE, lecture notes   
  Monday
13:15-15:00
MVF24 and MVF25 E11   Work on projects
May 11 Wednesday
10:00-11:45
Euler L12 Analysing microscopy data by RICS and SPRIA, lecture notes and LN pages 145-153  
  Wednesday
13:15-15:00
MVF24 and MVF25 E12   Work on projects
May 16 Monday Work on projects
May 18 Wednesday Work on projects
May 23 Monday 8:00-9:45 Euler L13 Project seminars  
  Monday
13:15-15:00
Euler E13  Project seminars  
May 25 Wednesday
10:00-11:45
Euler L14 Project seminars  
  Wednesday
13:15-15:00
Euler E14  Project seminars  

 

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Computer labs

The exercises will be done in Matlab, and some knowledge of Matlab is assumed. If you need an introduction, see Learning MATLAB, Tobin A. Driscoll ISBN: 978-0-898716-83-2 (The book is published by SIAM).

Most computer exercises will use functions written specifically for this course. These are collected in the following file: TMS016_Matlab.zip. Download this file and add the path to the folder in matlab: addpath('path_to_folder'). Then run the command tms016path to set the path to the files.

Data used in the exercies are colleded here: TMS016_Data.zip.


Reference literature:

Learning MATLAB, Tobin A. Driscoll ISBN: 978-0-898716-83-2 (The book is published by SIAM).

 

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Course summary:

Date Details Due