A minimum spanning forest based hyperspectral image classification method for cancerous tissue detection
نویسندگان
چکیده
Hyperspectral imaging is a developing modality for cancer detection. The rich information associated with hyperspectral images allow for the examination between cancerous and healthy tissue. This study focuses on a new method that incorporates support vector machines into a minimum spanning forest algorithm for differentiating cancerous tissue from normal tissue. Spectral information was gathered to test the algorithm. Animal experiments were performed and hyperspectral images were acquired from tumor-bearing mice. In vivo imaging experimental results demonstrate the applicability of the proposed classification method for cancer tissue classification on hyperspectral images.
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ورودعنوان ژورنال:
- Proceedings of SPIE--the International Society for Optical Engineering
دوره 9034 شماره
صفحات -
تاریخ انتشار 2014