Publication: CTScanTool, a semi-automated organ segmentation tool for radiotherapy treatment planning
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Issued Date
2019
Resource Type
File Type
application/pdf
ISSN
17426588
Other identifier(s)
2-s2.0-85073453351
Rights Holder(s)
มหาวิทยาลัยศรีนครินทรวิโรฒ
Bibliographic Citation
Journal of Physics: Conference Series. Vol 1285, No.1 (2019)
Suggested Citation
Liamsuwan T., Tantisatirapong S., Tangboonduangjit P. CTScanTool, a semi-automated organ segmentation tool for radiotherapy treatment planning. Journal of Physics: Conference Series. Vol 1285, No.1 (2019). doi:10.1088/1742-6596/1285/1/012027 Retrieved from: https://hdl.handle.net/20.500.14740/5155
Abstract
The goal of radiation therapy is to eradicate tumors while sparing normal tissues from radiation damage. Therefore, accurate definition of tumor and organ boundaries is important for achieving good treatment outcome. Segmentation of tumors and organs at risk is a standard procedure done by radiation oncologists for radiation therapy treatment planning, for which computed tomography (CT) images are commonly used. In this paper, we present the development of CTScanTool, the organ segmentation tool with a graphical user interface, allowing semi-automated and manual delineation. The proposed semi-automated segmentation method is based on the combined techniques of region growing, morphological reconstruction, and watershed transform algorithms. The semi-automated segmentation results of CT images were compared with those contoured by experienced radiation oncologists. In the experiment, we investigated the combined segmentation method on brain, lung and kidney tissues. In all cases, the true positive rate (sensitivity) was higher than 95%. Jaccard indices and positive predictive values (precision) were higher than 91% for brain and lung tissues and better than 81% for kidney tissues. In the near future, CTScanTool will be incorporated in the Proton pencil beam Scanning treatment PLANning system (PSPLAN) used for research and education in proton therapy. © 2019 Published under licence by IOP Publishing Ltd.
Subject(s)
Automation
Biological organs
Graphical user interfaces
Histology
Image segmentation
Proton beam therapy
Radiation damage
Radiotherapy
Tumors
Combined segmentations
Morphological reconstruction
Positive predictive values
Radiation therapy treatment planning
Radiotherapy treatment planning
Semi-automated segmentation
Treatment planning systems
Watershed transform algorithm
Computerized tomography
Biological organs
Graphical user interfaces
Histology
Image segmentation
Proton beam therapy
Radiation damage
Radiotherapy
Tumors
Combined segmentations
Morphological reconstruction
Positive predictive values
Radiation therapy treatment planning
Radiotherapy treatment planning
Semi-automated segmentation
Treatment planning systems
Watershed transform algorithm
Computerized tomography