Using fuzzy logics to determine optimal oversampling factor for voxelizing 3D surfaces in radiation therapy.
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| Title: | Using fuzzy logics to determine optimal oversampling factor for voxelizing 3D surfaces in radiation therapy. |
|---|---|
| Authors: | Pinter, C.1 (AUTHOR) csaba.pinter@queensu.ca, Olding, T.2 (AUTHOR), Schreiner, L. J.2 (AUTHOR), Fichtinger, G.1 (AUTHOR) |
| Source: | Soft Computing - A Fusion of Foundations, Methodologies & Applications. 2020, Vol. 24 Issue 24, p18959-18970. 12p. |
| Subjects: | Radiotherapy, Fuzzy systems, Algorithms, Fuzzy logic, Histograms |
| Abstract: | Voxelizing three-dimensional surfaces into binary image volumes is a frequently performed operation in medical applications. In radiation therapy (RT), dose-volume histograms (DVHs) calculated within such surfaces are used to assess the quality of an RT treatment plan in both clinical and research settings. To calculate a DVH, the 3D surfaces need to be voxelized into binary volumes. The voxelization parameters may considerably influence the output DVH. An effective way to improve the quality of the voxelized volume (i.e., increasing similarity between that and the original structure) is to apply oversampling to increase the resolution of the output binary volume. However, increasing the oversampling factor raises computational and storage demand. This paper introduces a fuzzy inference system that determines an optimal oversampling factor based on relative structure size and complexity, finding the balance between voxelization accuracy and computation time. The proposed algorithm was used to automatically calculate oversampling factor in four RT studies: two phantoms and two real patients. The results show that the method is able to find the optimal oversampling factor in most cases, and the calculated DVHs show good match to those calculated using manual overall oversampling of two. The algorithm can potentially be adopted by RT treatment planning systems based on the open-source implementation to maintain high DVH quality, enabling the planning system to find the optimal treatment plan faster and more reliably. [ABSTRACT FROM AUTHOR] |
| Copyright of Soft Computing - A Fusion of Foundations, Methodologies & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 147104474 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Using fuzzy logics to determine optimal oversampling factor for voxelizing 3D surfaces in radiation therapy. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Pinter%2C+C%2E%22">Pinter, C.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> csaba.pinter@queensu.ca</i><br /><searchLink fieldCode="AR" term="%22Olding%2C+T%2E%22">Olding, T.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schreiner%2C+L%2E+J%2E%22">Schreiner, L. J.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fichtinger%2C+G%2E%22">Fichtinger, G.</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Soft+Computing+-+A+Fusion+of+Foundations%2C+Methodologies+%26+Applications%22">Soft Computing - A Fusion of Foundations, Methodologies & Applications</searchLink>. 2020, Vol. 24 Issue 24, p18959-18970. 12p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Radiotherapy%22">Radiotherapy</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+systems%22">Fuzzy systems</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+logic%22">Fuzzy logic</searchLink><br /><searchLink fieldCode="DE" term="%22Histograms%22">Histograms</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Voxelizing three-dimensional surfaces into binary image volumes is a frequently performed operation in medical applications. In radiation therapy (RT), dose-volume histograms (DVHs) calculated within such surfaces are used to assess the quality of an RT treatment plan in both clinical and research settings. To calculate a DVH, the 3D surfaces need to be voxelized into binary volumes. The voxelization parameters may considerably influence the output DVH. An effective way to improve the quality of the voxelized volume (i.e., increasing similarity between that and the original structure) is to apply oversampling to increase the resolution of the output binary volume. However, increasing the oversampling factor raises computational and storage demand. This paper introduces a fuzzy inference system that determines an optimal oversampling factor based on relative structure size and complexity, finding the balance between voxelization accuracy and computation time. The proposed algorithm was used to automatically calculate oversampling factor in four RT studies: two phantoms and two real patients. The results show that the method is able to find the optimal oversampling factor in most cases, and the calculated DVHs show good match to those calculated using manual overall oversampling of two. The algorithm can potentially be adopted by RT treatment planning systems based on the open-source implementation to maintain high DVH quality, enabling the planning system to find the optimal treatment plan faster and more reliably. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Soft Computing - A Fusion of Foundations, Methodologies & Applications is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s00500-020-05126-w Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 12 StartPage: 18959 Subjects: – SubjectFull: Radiotherapy Type: general – SubjectFull: Fuzzy systems Type: general – SubjectFull: Algorithms Type: general – SubjectFull: Fuzzy logic Type: general – SubjectFull: Histograms Type: general Titles: – TitleFull: Using fuzzy logics to determine optimal oversampling factor for voxelizing 3D surfaces in radiation therapy. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Pinter, C. – PersonEntity: Name: NameFull: Olding, T. – PersonEntity: Name: NameFull: Schreiner, L. J. – PersonEntity: Name: NameFull: Fichtinger, G. IsPartOfRelationships: – BibEntity: Dates: – D: 05 M: 12 Text: 2020 Type: published Y: 2020 Identifiers: – Type: issn-print Value: 14327643 Numbering: – Type: volume Value: 24 – Type: issue Value: 24 Titles: – TitleFull: Soft Computing - A Fusion of Foundations, Methodologies & Applications Type: main |
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