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Paper Information

Journal:   IRANIAN JOURNAL OF MEDICAL PHYSICS   SUMMER 2010 , Volume 7 , Number 2 (27); Page(s) 21 To 39.
 
Paper: 

ASSESSMENT OF THE LOG-EUCLIDEAN METRIC PERFORMANCE IN DIFFUSION TENSOR IMAGE SEGMENTATION

 
 
Author(s):  CHARMI MOSTAFA, MAHLOOJI FAR ALI*
 
* DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING, TARBIAT MODARES UNIVERSITY, TEHRAN, IRAN
 
Abstract: 

Introduction: Appropriate definition of the distance measure between diffusion tensors has a deep impact on Diffusion Tensor Image (DTI) segmentation results. The geodesic metric is the best distance measure since it yields high-quality segmentation results. However, the important problem with the geodesic metric is a high computational cost of the algorithms based on it. The main goal of this paper is to assess the possible substitution of the geodesic metric with the Log-Euclidean one to reduce the computational cost of a statistical surface evolution algorithm.
Materials and Methods: We incorporated the Log-Euclidean metric in the statistical surface evolution algorithm framework. To achicve this goal, the statistics and gradients of diffusion tensor images were defined using the Log-Euclidean metric. Numerical implementation of the segmentation algorithm was performed in the MATLAB software using the finite difference techniques.
Results: In the statistical surface evolution framework, the Log-Euclidean metric was able to discriminate the torus and helix patterns in synthesis datasets and rat spinal cords in biological phantom datasets from the background better than the Euclidean and J-divergence metrics. In addition, similar results were obtained with the geodesic metric. However, the main advantage of the Log-Euclidean metric over the geodesic metric was the dramatic reduction of computational cost of the segmentation algorithm, at least by 70 times.
Discussion and Conclusion: The qualitative and quantitative results have shown that the Log-Euclidean metric is a good substitute for the geodesic metric when using a statistical surface evolution algorithm in DTIs segmentation.

 
Keyword(s): BIOLOGICAL PHANTOM, DIFFUSION TENSOR IMAGE, LOG-EUCLIDEAN METRIC, SEGMENTATION
 
 
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APA: Copy

CHARMI, M., & MAHLOOJI FAR, A. (2010). ASSESSMENT OF THE LOG-EUCLIDEAN METRIC PERFORMANCE IN DIFFUSION TENSOR IMAGE SEGMENTATION. IRANIAN JOURNAL OF MEDICAL PHYSICS, 7(2 (27)), 21-39. https://www.sid.ir/en/journal/ViewPaper.aspx?id=279888



Vancouver: Copy

CHARMI MOSTAFA, MAHLOOJI FAR ALI. ASSESSMENT OF THE LOG-EUCLIDEAN METRIC PERFORMANCE IN DIFFUSION TENSOR IMAGE SEGMENTATION. IRANIAN JOURNAL OF MEDICAL PHYSICS. 2010 [cited 2021October19];7(2 (27)):21-39. Available from: https://www.sid.ir/en/journal/ViewPaper.aspx?id=279888



IEEE: Copy

CHARMI, M., MAHLOOJI FAR, A., 2010. ASSESSMENT OF THE LOG-EUCLIDEAN METRIC PERFORMANCE IN DIFFUSION TENSOR IMAGE SEGMENTATION. IRANIAN JOURNAL OF MEDICAL PHYSICS, [online] 7(2 (27)), pp.21-39. Available: https://www.sid.ir/en/journal/ViewPaper.aspx?id=279888.



 
 
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