8D010: Front-End Vision and Multi-Scale Image Analysis

Autumn 2008


[Image of Scale-Space Cube]

An introduction to modern multi-scale image analysis
based on inspiration of biological vision.

A course given at the Department of Biomedical Engineering (Eindhoven University of Technology and University of Maastricht).

NB: This course is also open as "ASCI course a8" for the PhD Research Schools "ASCI" and "ImagO".

Tutor: Prof. Bart M. ter Haar Romeny, PhD, Eindhoven University of Technology / Maastricht University
Dates: 5 weeks. Lectures on Monday afternoons (013:30-17:15) from 25 August 2008 till 22 September 2008, with computer laboratories on Wednesday mornings (08:45-12:15) from 27 August 2008 till 24 September 2008, using Mathematica 6.0 to exercise the course material and tasks. In the week 8-12 September there is no course.

Total duration: 18 hours of 45 min. oral lectures and 20 hours hands-on training (5 blocks of 4 hours). Note: no courses in the week 8-12 September 2008.

Code TUE-BME: 8D010 (3 ECTS study points).
The lectures are recorded, and can be watched as streaming video on http://videocollege.tue.nl, course 8D010.

Goal:

Image analysis is the extraction of useful information from images. In this course we give a modern mathematical (and physics based) approach to multi-scale image analysis as a branch of computer vision. We give an intuitive introduction to multi-scale image analysis, trying to keep the analogy with stages in the human visual system as close as possible. The human visual system also widely exploits a diversity of multi-scale filters in its processing layers.

Among the topics covered are: filters to sample and analyze images, the use of filters in detecting edges and corners in images, multi-scale analysis of 2D and 3D shape and motion from image sequences, depth from stereo, orientation analysis, and the use of contemporary, well-understood mathematical tools in this field such as differential geometry and tensor analysis.

The majority of the examples discussed are from 2D, 3D and 4D (3D-time) medical imaging. We devote some time to the efficient numerical implementation of the different techniques. Hands-on experience is acquired in a computer lab, where experiments in Mathematica illustrate the theory and applications in practice.

Topics discussed:

A modern development is computer-aided diagnosis (CAD), where the computer assists in finding possible pathology in images, particularly in screening applications. We discuss some examples of this promising area: detection of stellate tumors in mammography, counting follicles for fertility related diagnosis with 3D ultrasound, and detecting polyps in 3D virtual colonoscopy.

We also discuss examples from molecular imaging. Special molecules can be designed with specific (ligand) binding locations, and with fluorescent markers making them visible with 3D fluorescence microscopy, with radioactive labels to detect them with SPECT and PET scanners, and/or contrast media to visualize them with MRI techniques. This leads to a high specificity for early cancer detection (and many other diseases). Computer vision plays an increasing role in the detection and recognition of structures, quantitative analysis, segmentation and visualization. 

Times:
Day Time Content Lecture material Room Assistant
Monday
25 August 2008
13:30-14:15 Course Introduction   Introduction
  Introduction (zipfile with all movies, 146 MB)
Matrix 1.44  
  14:30-15:15 Course Notion of scale Powers of 10 Matrix 1.44  
  15:30-16:15 Course Axiomatics of multi-scale operators   Scale-space from entropy Matrix 1.44  
  16:30-17:15 Course The Gaussian kernel,
regularization
Gaussian kernel Matrix 1.44  
Wednesday
27 August 2008
08:45-09:30 Computer lab Plenary lecture:
Introduction to Mathematica 6.0
Video of the revolutionary interactivity in Mathematica 6

Tutorial Mathematica notebooks 8ZZ16:

Cursus deel 1 van 3 (Dutch)
Cursus deel 2 van 3 (Dutch)
Cursus deel 3 van 3 (Dutch)


Course part 1 of 3 (English)
Course part 2 of 3 (English)

Course part 3 of 3 (English)
 


BMIA MMA course

WH 3A.06 Alessandro Becciu, Markus van Almsick
  09:30-12:45 Computer lab Exercising with Mathematica 6.0 Download the FEV book

MathVisionTools

FEV6.nb, FEV6.m
(store in directory C:\Documents and Settings\All Users\Application Data\Mathematica\Applications\FrontEndVision)

MathVisionTools

Exercises I
Exercises II

Some testimages to play with.
 

WH 3A.06 Alessandro Becciu, Markus van Almsick
 
 
Exercises with Mathematica 6.0 Study material:
Eindhoven Tips
Dictionary manipulations
Often used commands

FrondEnd Interactivity
Demo active shape
PackageNotebook.nb
Wolfram Inc.
Eduroam (network access through SurfNet)

  Alessandro Becciu, Markus van Almsick
Monday
1 September 2008
13:00-13:45 Course Gaussian derivatives, deblurring Gaussian derivatives
Deblurring
Deblurring
Matrix 1.44  
  14:00-14:45 Course Limits on observations, numeric implementation of
Gaussian derivatives
Limits
Limits
Convolution01
Convolution02
Convolution03
  Convolution animations
Implementation
 
Matrix 1.44  
  15:00-15:45 Course Gauge coordinates Differential structure Matrix 1.44  
Wednesday
3 September 2008
09:30-12:30 Computer Lab Exercising FEV lectures   WH 3A06 Alessandro Becciu, Markus van Almsick
Monday 8 September 2008 No lectures        
Wednesday 10 September 2008 09:30-12:45 Computer lab Exercising FEV lectures   WH3A.06 Alessandro Becciu, Markus van Almsick
Monday
15 September 2008
13:30-14:15 Course Differential structure I Applications second order structure Matrix 1.44  
  14:30-15:15 Course Differential structure II Vesselness Matrix 1.44  
  15:30-16:15 Course Front-end visual system I Front-End Visual System Matrix 1.44  
  16:30-17:15 Course Front-end visual system II Visual illusions
Spiral illusion
Matrix 1.44  
Wednesday
17 September 2008
09:30-12:30 Computer Lab Exercising FEV lectures   WH 3A06 Alessandro Becciu, Markus van Almsick
Monday
22 September 2007
13:30-14:15 Course Geometry-driven diffusion Geometry-Driven Diffusion
Geometry-Driven Diffusion
PDF: Original paper:
P. Perona, J. Malik, "Scale-space and edge detection using anisotropic diffusion", PAMI 12(7), pp. 629-639, 1990. 
Matrix 1.44  
  14:30-15:15 Course Color Differential Structure Color differential structure
Color differential structure
Matrix 1.44  
  15:30-16:15 Course Scale-time: differential structure of time sequences Scale-time
Scale-time
Matrix 1.44  
Wednesday
24 September 2008
08:45-09:30 Course Deep structure II:
toppoints,
image retrieval,
ScaleSpaceViz demo
Contextual operators

Toppoints in image matching
ScaleSpaceViz (VTK application) download

Matrix 1.44  
  09:45-10:30 Conclusions, Q&A   Matrix 1.44  
Wednesday
24 September 2008
13:30-17:00 Computer lab, Mathematica exercises Any topic of the course   WH 3A06 Alessandro Becciu, Markus van Almsick
 

Place:


*Lecture rooms:   see table above.
Matrix: Matrix building
WH: W-Hoog (Werktuigbouw-Hoog).
     WH3A.06 is a room with desktop computers, available for exercising the course material with Mathematica 6 (and 5.2).

See the campusmap of TU/e for directions.

Literature

The reader consists of the chapters of a the book: "Front-End Vision and Multi-scale Image Analysis", by Bart M. ter Haar Romeny. This book is written as a series of Mathematica notebooks. It contains a CR-ROM with all notebooks, which can be installed in the Mathematica Help-browser. The Mathematica code and exercises are the topic for the computer laboratories during the course. Please note that an upgrade is available to make the notebooks compatible with the current Mathematica version 6.0.

ISBN: 1-4020-1507-0 (paperback), 1-4020-1503-8 (hardcover). Springer, Berlin. 
Order the book with Springer or Amazon.

NB: The publisher has reported that 'printing on demand' is delayed. The book can also be downloaded with all chapters, Mathematica notebooks and example images from
here (login with your TU/e domain user/password).

Recommended reading:

Proceedings Scale-Space conferences

Other software:

Other:

Computer Laboratory:

On the Wednesday mornings computer laboratories will be organized to acquire hands-on experience with the discussed scaled differential invariant operators on a variety of 2D and 3D images. We use the program Mathematica 6.0 (http://www.wolfram.com/).

For TUE members: Mathematica 6.0 (and the previous version 5.2) can be downloaded from the TU/e campus software website.

Recommended tutorial books on Mathematica:

 Some useful notebooks:

The famous mathematics teaching files and resource online: MathWorld.


Examination:

For BME students: select any three (3) questions from this set of questions: Exam tasks BME 2008.

Write a small notebook per question (max. 1-2 A4 each) and send them within two weeks after the end of the course to B.M.terHaarRomeny@tue.nl.


Some examples

The detection of ridges (midlines) for an X-ray image of hands. "Ridgeness" is a second order property.

Low dose fluoroscopy image of an electro-physiology catheter in ther heart. The extra low dose is beneficial for the radiation dose, but leads to a deteriorated image quality. Robust catheter detection with oriented filters and tensor voting.

Left: histological image of a fungus cell, paramecium caudatum. Middle: edge detection with a detector optimized for yellow-blue differences. Right: edge detection with a detector optimized for red-green differences.

Cerebral aneurysm from 3D CT angiography. The same aneurysm cleaned with an adaptive edge-preserving 3D denoising filter.

Contact the tutor:

prof.dr.ir. Bart M. ter Haar Romeny, email: B.M.terHaarRomeny@tue.nl

Department of Biomedical Engineering (BME-BMT)
Group Biomedical Imaging Analysis BMIA
Eindhoven University of Technology
Den Dolech 2 - WH2.106
NL-5612 AZ Eindhoven
Tel. 040-2475537 (secr. Margret Philips).

FEV class of 2008 - BME course.