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

Tumor 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.

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