Kidney Segmentation in CT Data Using Hybrid Level-Set Method with Ellipsoidal Shape Constraints
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 visualiza...
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| Format: | Article |
| Language: | English |
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Polish Academy of Sciences
2017-03-01
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| Series: | Metrology and Measurement Systems |
| Subjects: | |
| Online Access: | http://www.degruyter.com/view/j/mms.2017.24.issue-1/mms-2017-0006/mms-2017-0006.xml?format=INT |
| _version_ | 1819008564806549504 |
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| author | Skalski Andrzej Heryan Katarzyna Jakubowski Jacek Drewniak Tomasz |
| author_facet | Skalski Andrzej Heryan Katarzyna Jakubowski Jacek Drewniak Tomasz |
| author_sort | Skalski Andrzej |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-21T00:42:29Z |
| format | Article |
| id | doaj.art-ef82540f6d134e61aeeeed4c403f6519 |
| institution | Directory Open Access Journal |
| issn | 2300-1941 |
| language | English |
| last_indexed | 2024-12-21T00:42:29Z |
| publishDate | 2017-03-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | Metrology and Measurement Systems |
| spelling | doaj.art-ef82540f6d134e61aeeeed4c403f65192022-12-21T19:21:37ZengPolish Academy of SciencesMetrology and Measurement Systems2300-19412017-03-0124110111210.1515/mms-2017-0006mms-2017-0006Kidney Segmentation in CT Data Using Hybrid Level-Set Method with Ellipsoidal Shape ConstraintsSkalski Andrzej0Heryan Katarzyna1Jakubowski Jacek2Drewniak Tomasz31) AGH University of Science and Technology, Department of Measurement and Electronics, Al. Mickiewicza 30, Cracow, Poland1) AGH University of Science and Technology, Department of Measurement and Electronics, Al. Mickiewicza 30, Cracow, Poland2) Rydygier Memorial Hospital, Department of Urology, Os. Złotej Jesieni 1, 31-826 Cracow, Poland3) Specialized Municipal Hospital G. Narutowicz, Department of Urology, Prądnicka 35-37, 31-202 Cracow, PolandWith 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.http://www.degruyter.com/view/j/mms.2017.24.issue-1/mms-2017-0006/mms-2017-0006.xml?format=INTLevel Set methodkidneyCT dataimage segmentationellipsoid |
| spellingShingle | Skalski Andrzej Heryan Katarzyna Jakubowski Jacek Drewniak Tomasz Kidney Segmentation in CT Data Using Hybrid Level-Set Method with Ellipsoidal Shape Constraints Metrology and Measurement Systems Level Set method kidney CT data image segmentation ellipsoid |
| title | Kidney Segmentation in CT Data Using Hybrid Level-Set Method with Ellipsoidal Shape Constraints |
| title_full | Kidney Segmentation in CT Data Using Hybrid Level-Set Method with Ellipsoidal Shape Constraints |
| title_fullStr | Kidney Segmentation in CT Data Using Hybrid Level-Set Method with Ellipsoidal Shape Constraints |
| title_full_unstemmed | Kidney Segmentation in CT Data Using Hybrid Level-Set Method with Ellipsoidal Shape Constraints |
| title_short | Kidney Segmentation in CT Data Using Hybrid Level-Set Method with Ellipsoidal Shape Constraints |
| title_sort | kidney segmentation in ct data using hybrid level set method with ellipsoidal shape constraints |
| topic | Level Set method kidney CT data image segmentation ellipsoid |
| url | http://www.degruyter.com/view/j/mms.2017.24.issue-1/mms-2017-0006/mms-2017-0006.xml?format=INT |
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