Consistency and Comparison of Monomodal Multi-Temporal Medical Image Registration-Segmentation and Mathematical Model for Glioblastoma Volume Progression

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dc.contributor.authorIrmak, Emrah
dc.date.accessioned2026-01-24T12:00:58Z
dc.date.available2026-01-24T12:00:58Z
dc.date.issued2020
dc.departmentAlanya Alaaddin Keykubat Üniversitesi
dc.description.abstractTumor volume progression analysis and tumor volume measurement are very common tasks in cancer research and image processing fields. Tumor volume measurement can be carried out in two ways. The first way is to use different mathematical formulas and the second way is to use image registration method. In this paper, using 3D medical image registration-segmentation algorithm, multiple scans of MR images of a patient who has brain tumor are registered with different MR images of the same patient acquired at a different time so that growth of the tumor inside the patient's brain can be investigated. Tumor volume progression analysis and tumor volume measurement are performed using image registration technique and the results are compared with the results of tumor volume measurement by mathematical formulas. For the first patient, grown brain tumor volume is found to be 10345 mm³, diminished brain tumor volume is found to be 15278 mm³ and unchanged brain tumor volume is found to be 20876 mm³. Numerical results obtained by image registration model proves that medical image - registration method is not only between the true ranges but also is very close to the best mathematical formula. Medical image registration-segmentation are implemented to 19 patients and satisfactory results are obtained The results are compared with the results obtained from mathematical methods. An advantageous point of medical image registration-segmentation method over mathematical models for brain tumor investigation is that grown, diminished, and unchanged brain tumor parts of the patients are investigated and computed on an individual basis in a three - dimensional (3D) manner within the time.
dc.identifier.doi10.17694/bajece.733330
dc.identifier.endpage341
dc.identifier.issn2147-284X
dc.identifier.issue4
dc.identifier.startpage331
dc.identifier.trdizinid468981
dc.identifier.urihttps://search.trdizin.gov.tr/tr/yayin/detay/468981
dc.identifier.urihttps://doi.org/10.17694/bajece.733330
dc.identifier.urihttps://hdl.handle.net/20.500.12868/3873
dc.identifier.volume8
dc.indekslendigikaynakTR-Dizin
dc.language.isoen
dc.relation.ispartofBalkan Journal of Electrical and Computer Engineering
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_TR-Dizin_20260121
dc.subjectTıbbi İnformatik,Görüntüleme Bilimi ve Fotoğraf Teknolojisi,Mikrobiyoloji,Nörolojik Bilimler,Onkoloji
dc.titleConsistency and Comparison of Monomodal Multi-Temporal Medical Image Registration-Segmentation and Mathematical Model for Glioblastoma Volume Progression
dc.typeArticle

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