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Interactive modeling and evaluation of tumor growth

TitleInteractive modeling and evaluation of tumor growth
Publication TypeJournal Article
Year of Publication2010
AuthorsKoff, D., J. Scharcanski, L. da Silva, and A. Wong
JournalJournal of Digital Imaging
Pagination755 - 768
KeywordsActive contours, cancer detection, chest radiographs, Computed tomography (CT), computer analysis, Computer Vision, computer-assisted diagnosis, Diagnostic Imaging, digital image processing, image segmentation, lung cancer

This paper addresses the need to quantify tumor growth and detect changes as this information is relevant to manage the patient treatment and to aid biotechnological efforts to cure cancer (Silva et al. 2008). An interactive tumor segmentation technique is used to recover the shape and size of tumors without imposing shape constraints. This segmentation algorithm provides good convergence, is robust to the initialization conditions, and requires simple and intuitive user interactions. A parametric approach to model tumor growth analytically is proposed in this paper. The preliminary experimental results are encouraging. The segmentation method is shown to be robust and simple to use, even in situations where the tumor boundary definition is challenging. Also, the experiments indicate that the proposed model potentially can be used to extrapolate the available data and help predict the tumor size (assuming unconstrained growth). Additionally, the proposed method potentially can provide a quantitative reference to compare the tumor shrinkage rate in cancer treatments.