Partial Differential Equations-Based Segmentation for Radiotherapy Treatment Planning
The purpose of this study is to develop automatic algorithms for the segmentation phase of radiotherapy treatmentplanning. We develop new image processing techniques that are based on solving a partial differential equation for theevolution of the curve that identifies the segmented organ. The vel...
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| Format: | Article |
| Language: | English |
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AIMS Press
2005-02-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2005.2.209 |
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| author | Frédéric Gibou Doron Levy Carlos Cárdenas Pingyu Liu Arthur Boyer |
| author_facet | Frédéric Gibou Doron Levy Carlos Cárdenas Pingyu Liu Arthur Boyer |
| author_sort | Frédéric Gibou |
| collection | DOAJ |
| description | The purpose of this study is to develop automatic algorithms for the segmentation phase of radiotherapy treatmentplanning. We develop new image processing techniques that are based on solving a partial differential equation for theevolution of the curve that identifies the segmented organ. The velocity function is based on the piecewiseMumford-Shah functional. Our method incorporates information about the target organ into classical segmentationalgorithms. This information, which is given in terms of a three-dimensional wireframe representation of the organ,serves as an initial guess for the segmentation algorithm. We check the performance of the new algorithm on eight datasets of three different organs: rectum, bladder, and kidney. The results of the automatic segmentation were comparedwith a manual segmentation of each data set by radiation oncology faculty and residents. The quality of the automaticsegmentation was measured with the ''$\kappa$-statistics'', and with a count of over- and undersegmented frames, andwas shown in most cases to be very close to the manual segmentation of the same data. A typical segmentation of anorgan with sixty slices takes less than ten seconds on a Pentium IV laptop. |
| format | Article |
| id | doaj-art-9c5889bb2e474800a8562080908e1eca |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2005-02-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-9c5889bb2e474800a8562080908e1eca2025-01-24T01:48:05ZengAIMS PressMathematical Biosciences and Engineering1551-00182005-02-012220922610.3934/mbe.2005.2.209Partial Differential Equations-Based Segmentation for Radiotherapy Treatment PlanningFrédéric Gibou0Doron Levy1Carlos Cárdenas2Pingyu Liu3Arthur Boyer4Department of Computer Science and Department of Mechanical Engineering, University of California at Santa Barbara, CA 93106-5070Department of Mathematics, Stanford University, Stanford, CA 94305-2125Siemens Medical Solutions, Med SW West, 755 College Road East, Princeton, NJ 08540Department of Radiation Oncology, Stanford University, Stanford, CA 94305Department of Radiation Oncology, Stanford University, Stanford, CA 94305The purpose of this study is to develop automatic algorithms for the segmentation phase of radiotherapy treatmentplanning. We develop new image processing techniques that are based on solving a partial differential equation for theevolution of the curve that identifies the segmented organ. The velocity function is based on the piecewiseMumford-Shah functional. Our method incorporates information about the target organ into classical segmentationalgorithms. This information, which is given in terms of a three-dimensional wireframe representation of the organ,serves as an initial guess for the segmentation algorithm. We check the performance of the new algorithm on eight datasets of three different organs: rectum, bladder, and kidney. The results of the automatic segmentation were comparedwith a manual segmentation of each data set by radiation oncology faculty and residents. The quality of the automaticsegmentation was measured with the ''$\kappa$-statistics'', and with a count of over- and undersegmented frames, andwas shown in most cases to be very close to the manual segmentation of the same data. A typical segmentation of anorgan with sixty slices takes less than ten seconds on a Pentium IV laptop.https://www.aimspress.com/article/doi/10.3934/mbe.2005.2.209segmentationradiotherapy treatmentlevel-set methodsmumford-shah. |
| spellingShingle | Frédéric Gibou Doron Levy Carlos Cárdenas Pingyu Liu Arthur Boyer Partial Differential Equations-Based Segmentation for Radiotherapy Treatment Planning Mathematical Biosciences and Engineering segmentation radiotherapy treatment level-set methods mumford-shah. |
| title | Partial Differential Equations-Based Segmentation for Radiotherapy Treatment Planning |
| title_full | Partial Differential Equations-Based Segmentation for Radiotherapy Treatment Planning |
| title_fullStr | Partial Differential Equations-Based Segmentation for Radiotherapy Treatment Planning |
| title_full_unstemmed | Partial Differential Equations-Based Segmentation for Radiotherapy Treatment Planning |
| title_short | Partial Differential Equations-Based Segmentation for Radiotherapy Treatment Planning |
| title_sort | partial differential equations based segmentation for radiotherapy treatment planning |
| topic | segmentation radiotherapy treatment level-set methods mumford-shah. |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2005.2.209 |
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