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3D and 4D Adaptive Filtering for Image Denoising and Patient Safety


 

Research Group

Prof. Hans Knutsson Project manager, Supervisor IMT, CMIV
Mats Andersson, PhD Research Engineer, Asst. Supervisor IMT, CMIV
Anders Eklund, Tech. lic. PhD Student IMT, CMIV
Gustaf Johansson, M.Sc. PhD Student IMT, CMIV
Johan Wiklund, Tech. lic. Research Engineer IMT, CMIV
Martin Hedlund, M.Sc. Technical Director ContextVision
Gunnar Farnebäck, PhD Image Processing Expert ContextVision
Michael Sandborg, PhD Medical physicist IMH, CMIV
Prof. Örjan Smedby, MD Radiologist IMH, CMIV

Former members

Björn Svensson, PhD PhD Student IMT, CMIV

 

Results of 4D adaptive filtering on 4D CT-heart with ECG gated exposure


 

  The image shows the original CT data to the left and the denoised CT data to the right. Two movies that show the original 4D CT data and the denoised CT data can be found at Movie 1, Movie 2
 

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 rapidly increasing. This project focuses on efficient methods for local feature extraction and enhancement of multidimensional images and can be traced back to 2003 when a research cooperation was formed by the Medical Informatics group at IMT, CMIV and ContextVision AB.
  The project were initially funded by The Swedish Agency for Innovation Systems, VINNOVA (VINST) and by The Swedish Foundation for Strategic Research, SSF (Forska&Väx). A fundamental approach was to develop a methodology for efficient implementations of multidimensional filter banks. The Filter networks concept was developed where the number of filter coefficients can significantly be reduced by sequential convolution, using sparse intermediary filter components. A 3D filter network for estimation of local structure and adaptive filtering can reduce the computational load by a factor exceeding 70 compared to a conventional filtering approach. The first product incorporating this technology, GOPiCE US - real-time volumetric ultrasound image enhancement, was launched in April 2009 by ContextVision AB and the first customer contract was signed in October 2010.
  Since 2008 the project is funded by the Swedish Research Council VR (3D and 4D Adaptive Filtering for Image Denoising and Patient Safety, dnr 2008-3813). The power of dimensionality is further explored by working with clinical 4D CT-heart volume sequences where the patient safety is focused both in terms of decreased X-ray exposure and improved diagnostic image quality. Current developments of the research group comprise advanced tuning strategies to account for the variability present in the imaging parameters, e.g. ECG gated exposure in 4D CT-heart, anisotropic sampling of 4D data, anisotropic noise structure, local mass density dependent SNR and local structure specific noise thresholds. Within the project a new efficient method to estimate local structure and to generalize the phase concept has been developed using Monomial filters. The Adaptive filtering of 4D CT-Heart has also been implemented on GPGPU (General-Purpose Computation on Graphics Hardware) which provide 4D data to be processed within a few minutes. The next major step within this research field will be to develop a user friendly interface for handling the variability of denoising parameters across organs, regions and tissues.
 
 

Publications

True 4D Image Denoising on the GPU by A. Eklund, M. Andersson, H. Knutsson, International Journal of Biomedical Imaging, Article ID 952819, 2011.[PDF]

Structure Tensor Estimation - Introducing Monomial Quadrature Filter Sets by H. Knutsson, C-F. Westin, M. Andersson, New Developments in the Visualization and Processing of Tensor Fields, Dagstuhl 2009, 2011

4D Adaptive Filtering of CT-Heart by M. Andersson, M. Sandborg, Ö. Smedby, H. Knutsson, Proceedings of the SSAB Symposium on Image Analysis, 2011

Representing Local Structure using Tensors II by H. Knutsson, C-F. Westin, M. Andersson, Proceedings of the 17th Scandinavian conference on image analysis (SCIA 2011).[Paper]

Adaptive Filtering of 4D-heart CT for Image Denoising and Patient Safety by M. Andersson, Ö. Smedby, M. Sandborg, G. Farnebäck, H. Knutsson, Proceedings för Medicinteknikdagarna, 2010

A Multidimensional Filtering Framework with Applications to Local Structure Analysis and Image Enhancement by B. Svensson, Phd Thesis, Linköping University, Sweden, April 2008. [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]

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Senast uppdaterad: 2012-03-28