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

**Autumn****
2008**

## An introduction to modern multi-scale image analysis |

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.

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.

- Notion of scale in physics and mathematics
- Physics of observation, apertures
- Axiomatic derivation of filters
- Differentiation, scale and regularization
- History of scale-space theory
- The human visual pathway, receptive field structure
- Retinal distribution of receptive fields, feedback in the visual system
- Information processing in the visual cortex
- Gaussian derivatives and the diffusion equation
- Some differential geometry on images in 2D, 3D, 2D-time for robust feature detection and shape analysis
- Geometric invariants, landmarks
- Applications in medical imaging: computer-aided detection
- Mathematical morphology, incl. the slope transform
- Nonlinear, geometry-driven diffusion (evolution of images by partial differential equations)
- Deep structure of images, watershed segmentation
- Orientation analysis
- Summary

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: |
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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. |

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. |

Recommended reading:

- L. M. J. Florack: The Structure of Scalar Images. Computational Imaging and Vision Series, Dordrecht, Kluwer Academic Publishers, 1996.
- B. M. ter Haar Romeny, Ed.: Geometry-Driven Diffusion in Computer Vision. Dordrecht, Kluwer Academic Publishers, 1994.
- L. M. J. Florack: Visuele Perceptie en Digitale Beeldverwerking, Nieuw Archief voor Wiskunde, vol. 5/3, no. 1, pp. 34-41, maart 2002. PDF
- B. M. ter Haar Romeny: Computer Vision and Mathematica. Computing and Visualization in Science, vol. 5, no.1, pp. 53-65, Springer, 2002. PDF (1.7MB), Mathematica 4 Notebook (3.1MB).
- T. Lindeberg: Scale-Space Theory in Computer Vision, Dordrecht, Kluwer Academic Publishers, 1994.
- J. Sporring, M. Nielsen, L. Florack and P. Johansen (Eds.): Gaussian Scale-Space, Dordrecht, Kluwer Academic Publishers, 1996.
- J. Weickert: Anisotropic Diffusion in Image Processing, ECMI Series, Teubner-Verlag, Stuttgart, Germany, 1998. 170 pages, hardcover. ISBN 3-519-02606-6.
- WebVision: the visual cortex.
- Wikipedia on scale-space.

Proceedings Scale-Space conferences

- B. M. ter Haar Romeny, L. M. J. Florack, J. J. Koenderink, and M. A. Viergever, eds., Scale-Space '97: Proc. First Internat. Conf. on Scale-Space Theory in Computer Vision, Utrecht, vol. 1252 of Lecture Notes in Computer Science. Berlin: Springer Verlag, 1997.
- M. Nielsen, P. Johansen, O.F. Olsen, J. Weickert: Scale-Space Theories in Computer Vision, second International Conference, Scale-Space 1999, Corfu, Greece, September 26-27, 1999, vol. 1682 of Lecture Notes in Computer Science. Berlin: Springer Verlag, 1999.
- M. Kerckhove: Scale-Space and Morphology in Computer Vision, Third International Conference, Scale-Space 2001, Vancouver, Canada, July 7-8, 2001, vol. 2106 of Lecture Notes in Computer Science. Berlin: Springer Verlag, 2001.
- L.D. Griffin, M. Lillholm: Scale-Space Methods in Computer Vision, Fourth International Conference, Scale-Space 2003, Isle of Skye, UK, June 10-12, 2003, vol. 2695 of Lecture Notes in Computer Science. Berlin: Springer Verlag, 2003.
- R. Kimmel, N. Sochen, and J. Weickert, Fifth International Conf. on Scale Space and PDE methods in Computer Vision, Hofgeismar, Germany, April 2005, vol. 3459 of Lecture Notes in Computer Science. Berlin: Springer Verlag, 2005.

Other software:

- MathVisionTools, a toolbox for mathematical multi-scale computer vision operations. Written by Markus van Almsick, TU Eindhoven.
- ScaleSpaceViz, a package to visualize the deep structure of images. Written by Frans Kanters, TU Eindhoven.

Other:

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*:

- N. Blachman & C.P. Williams: "Mathematica, a practical appraoch".Prentice Hall 1999, second edition. ISBN 0-13-259201-0.
- H. Ruskeepää: "Mathematica Navigator, graphics and methods of applied mathematics", Academic Press 1999, ISBN 0-12-603640-3 (paperback with CD-ROM).
- J. Glynn & Th. Gray: "The beginner's guide to Mathematica version 4", Cambridge University press, 2000, ISBN 0-521-77153-6 (hardback, 0-521-77769-0 (paperback).
- R. M. Maeder: "Computer Science with Mathematica 4. Theory and practice for science, mathematics and engineering", Cambridge University Press, 2000, ISBN 0-521-631172-6 (hardback), 0-521-66395-4 (paperback).

Some useful notebooks:

- Introduction to the Fourier Transform
- Introduction to linear systems

The famous mathematics teaching files and resource online: MathWorld.

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.

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, |

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

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.