Meningioma (Brain Tumor) Classification using an Adaptive Discriminant Wavelet Packet Transform (2009)
Abstract / truncated to 115 words
Meningioma subtypes classification is a real world problem from the domain of histological image analysis that requires new methods for its resolution. Computerised histopathology presents a whole new set of problems and introduces new challenges in image classification. High intra-class variation and low inter-class differences in textures is often an issue in histological image analysis problems such as Meningioma subtypes classification. In this thesis, we present an adaptive wavelets based technique that adapts to the variation in the texture of meningioma samples and provides high classification accuracy results. The technique provides a mechanism for attaining an image representation consisting of various spatial frequency resolutions that represent the image and are referred to as subbands. Each ...
wavelet – wavelet packets – multiresolution analysis – brain tumours – image classification – medical image analysis
Information
- Author
- Qureshi, Hammad
- Institution
- University of Warwick
- Supervisor
- Publication Year
- 2009
- Upload Date
- Jan. 12, 2010
The current layout is optimized for mobile phones. Page previews, thumbnails, and full abstracts will remain hidden until the browser window grows in width.
The current layout is optimized for tablet devices. Page previews and some thumbnails will remain hidden until the browser window grows in width.