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Metrology and Measurement Systems

The Journal of Committee on Metrology and Scientific Instrumentation of Polish Academy of Sciences

4 Issues per year


IMPACT FACTOR 2016: 1.598

CiteScore 2016: 1.58

SCImago Journal Rank (SJR) 2016: 0.460
Source Normalized Impact per Paper (SNIP) 2016: 1.228

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ISSN
2300-1941
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Volume 24, Issue 1 (Mar 2017)

Issues

Kidney Segmentation in CT Data Using Hybrid Level-Set Method with Ellipsoidal Shape Constraints

Andrzej Skalski
  • Corresponding author
  • 1) AGH University of Science and Technology, Department of Measurement and Electronics, Al. Mickiewicza 30, Cracow, Poland
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  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Katarzyna Heryan
  • 1) AGH University of Science and Technology, Department of Measurement and Electronics, Al. Mickiewicza 30, Cracow, Poland
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  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Jacek Jakubowski / Tomasz Drewniak
Published Online: 2017-03-20 | DOI: https://doi.org/10.1515/mms-2017-0006

Abstract

With development of medical diagnostic and imaging techniques the sparing surgeries are facilitated. Renal cancer is one of examples. In order to minimize the amount of healthy kidney removed during the treatment procedure, it is essential to design a system that provides three-dimensional visualization prior to the surgery. The information about location of crucial structures (e.g. kidney, renal ureter and arteries) and their mutual spatial arrangement should be delivered to the operator. The introduction of such a system meets both the requirements and expectations of oncological surgeons. In this paper, we present one of the most important steps towards building such a system: a new approach to kidney segmentation from Computed Tomography data. The segmentation is based on the Active Contour Method using the Level Set (LS) framework. During the segmentation process the energy functional describing an image is the subject to minimize. The functional proposed in this paper consists of four terms. In contrast to the original approach containing solely the region and boundary terms, the ellipsoidal shape constraint was also introduced. This additional limitation imposed on evolution of the function prevents from leakage to undesired regions. The proposed methodology was tested on 10 Computed Tomography scans from patients diagnosed with renal cancer. The database contained the results of studies performed in several medical centers and on different devices. The average effectiveness of the proposed solution regarding the Dice Coefficient and average Hausdorff distance was equal to 0.862 and 2.37 mm, respectively. Both the qualitative and quantitative evaluations confirm effectiveness of the proposed solution.

Keywords: Level Set method; kidney; CT data; image segmentation; ellipsoid

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About the article

Received: 2016-06-07

Accepted: 2016-08-28

Published Online: 2017-03-20

Published in Print: 2017-03-01


Citation Information: Metrology and Measurement Systems, ISSN (Online) 2300-1941, DOI: https://doi.org/10.1515/mms-2017-0006.

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© 2017 Polish Academy of Sciences. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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