Validation of Performance Homogeneity of Chan-Vese Model on Selected Tumour Cells
dc.contributor.author | Appati, J.K. | |
dc.contributor.author | Badzi, F.I. | |
dc.contributor.author | Soli, M.A.T. | |
dc.contributor.author | Nwolley, S.J. | |
dc.contributor.author | Denwar, I.W. | |
dc.date.accessioned | 2021-11-04T10:10:33Z | |
dc.date.available | 2021-11-04T10:10:33Z | |
dc.date.issued | 2021 | |
dc.description | Research Article | en_US |
dc.description.abstract | This study aims to analyze the Chan-Vese model’s performance using a variety of tumor images. The processes involve the tumors’ segmentation, detecting the tumors, identifying the segmented tumor region, and extracting the features before classification occurs. In the findings, the Chan-Vese model performed well with brain and breast tumor segmentation. The model on the skin performed poorly. The brain recorded DSC 0.6949903, Jaccard 0.532558; the time elapsed 7.389940 with an iteration of 100. The breast recorded a DSC of 0.554107, Jaccard 0.383228; the time elapsed 9.577161 with an iteration of 100. According to this study, a higher DSC does not signify a well-segmented image, as the breast had a lower DSC than the skin. The skin recorded a DSC of 0.620420, Jaccard 0.449717; the time elapsed 17.566681 with an iteration of 200. | en_US |
dc.identifier.other | DOI: 10.4018/IJEHMC.20211101.oa7 | |
dc.identifier.uri | http://ugspace.ug.edu.gh/handle/123456789/37017 | |
dc.language.iso | en | en_US |
dc.publisher | International Journal of E-Health and Medical Communications | en_US |
dc.subject | Chan-Vese | en_US |
dc.subject | Deformable Models | en_US |
dc.subject | Dice Similarity Coefficient | en_US |
dc.subject | Level Set | en_US |
dc.subject | Tumor | en_US |
dc.title | Validation of Performance Homogeneity of Chan-Vese Model on Selected Tumour Cells | en_US |
dc.type | Article | en_US |
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