Research Group

Prof. Hans Knutsson	Project manager, Supervisor	IMT, CMIV
Mats Andersson, PhD	Research Engineer, Asst. Supervisor	IMT, CMIV
Björn Svensson, MSc	PhD Student	IMT, CMIV
Johan Wiklund, Tech. lic.	Research Engineer	IMT, CMIV
Klas Themner, PhD	R & D Manager	ContextVision
Martin Hedlund, MSc	Technical Director	ContextVision
Hagen Spies, PhD	Senior Scientist	ContextVision
Prof. Örjan Smedby, MD	Radiologist	IMV, CMIV
Lars Wigström, PhD	Research Engineer	IMV, CMIV

Introduction

Most signal processing tools, for feature extraction, image enhancement and visualization are limited to 2D, while multidimensional imaging of the human body is clinical routine. The computational complexity significantly increases, when extending dimensionality beyond 2D. The need for efficient filtering on volumes and volume sequences is therefore increasing.
 
This project focuses on efficient methods for local feature extraction and enhancement of multidimensional images. The fundamental approach is to find a methodology to achieve efficient implementations of filter networks for applications needed by ContextVision AB.
 
The number of filter coefficients can significantly be reduced by sequential convolution, using sparse intermediary filter components. Filter networks are especially useful, when a filter set is required. Filter components then can contribute to multiple outputs.
 
A 3D filter network for estimationg local structure and orientation has been developed within the project. The filter network have 9 different outputs and consists of 335 real filter coefficients. A corresponding filter set can be achieved by using 6 quadrature filters and standard convolution. This requires at least 6 x 13 x 13 x 13 complex coefficients, roughly 26 000 real coefficents. The computational load, in this case, is reduced by a factor exceeding 70 using the filter network approach.
 
The project is supported through the VINST programme funded by The Swedish Agency for Innovation Systems, Vinnova and The Swedish Foundation for Strategic Research, SSF. The programme supports research efforts, performed by research groups in close collaboration with high technological companies. This project started October 1, 2003 and has been granted approximately 150 kEuro/year.
 

Publications

Fast Multi-dimensional Filter Networks, Design, Optimization and Implementation by B. Svensson, Licentiate Thesis, Linköping University, Sweden, April 2006. [Abstract]

Efficient 3-D Adaptive Filtering for Medical Image Enhancement by B. Svensson, M. Andersson, Ö. Smedby and H. Knutsson, Proceedings of the {ISBI} IEEE International Symposium on Biomedical Imaging, Arlington, USA, April 2006. [Abstract]

Radiation Dose Reduction by Efficient 3D Image Restoration by B. Svensson, M. Andersson, Ö. Smedby and H. Knutsson, Proceedings of the {ECR} European Congress on Radiology, Vienna, Austria, March 2006. [Abstract]

Sparse Approximation for FIR Filter Design by B. Svensson, M. Andersson and H. Knutsson, Proceedings of the {SSBA} Symposium on Image Analysis, Umeå, Sweden, March 2006. [Abstract]

Performance Analysis of Filternets by H. Einarsson, Master Thesis, Linköping University, Sweden, February 2006. [Abstract]

Filter Networks for Efficient Estimation of Local 3D Structure by B. Svensson, M. Andersson and H. Knutsson, Proceedings of the Proceedings of the IEEE-ICIP, Genoa, Italy, September 2005. [Abstract]

Implications of Invariance and Uncertainty for Local Structure Analysis Filter Sets by H. Knutsson and M. Andersson, Signal Processing: Image Communications, July 2005. [PDF]

A Graph Representation of Filter Networks by B. Svensson, M. Andersson and H. Knutsson, Proceedings of the 14th Scandinavian conference on image analysis (SCIA'05), Joensuu, Finland, June 2005. [Abstract]

Design of Fast Multidimensional Filters Using Genetic Algorithms by M. Langer and B. Svensson and A. Brun and M. Andersson and H. Knutsson, Proceedings of EvoIASP, 7th European Workshop on Evolutionary Computing in Image Analysis and Signal Processing, Lausanne, Schweiz, March 2005. [PDF]

Design of Fast Multidimensional Filters by Genetic Algorithms by M. Langer, Master Thesis, Linköping University, Sweden, November 2004. [PDF]

Issues on Filter Networks for Efficient Convolution by B. Svensson, M. Andersson, J. Wiklund and H. Knutsson, Proceedings of the {SSBA} Symposium on Image Analysis, Uppsala, Sweden, March 2004. [PDF]

 

Related Articles

What's So Good About Quadrature Filters? by H. Knutsson and M. Andersson, Proceedings of the {ICIP} IEEE International Conference on Image Processing, Barcelona, Spain, September 2003. [PDF]
 
Loglets: Generalized Quadrature and Phase using Spherical Harmonics by H. Knutsson and M. Andersson, Proceedings of the {SCIA} Scandinavian Conference on Image Analysis, Göteborg, Sweden, June 2003.  [PDF]