Interactive Modeling and Evaluation of Tumor Growth
| Autor: | Luciano Silva da Silva, Alexander Wong, David Koff, Jacob Scharcanski |
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| Rok vydání: | 2009 |
| Předmět: |
Computer science
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Boundary (topology) Initialization Machine learning computer.software_genre Models Biological Article Neoplasms Digital image processing Convergence (routing) Medical imaging Humans Radiology Nuclear Medicine and imaging Segmentation Computer vision Parametric statistics Radiological and Ultrasound Technology business.industry Image segmentation Tumor Burden Computer Science Applications ComputingMethodologies_PATTERNRECOGNITION Artificial intelligence business computer Follow-Up Studies |
| Zdroj: | Journal of Digital Imaging. 23:755-768 |
| ISSN: | 1618-727X 0897-1889 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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