A Robust Adaptive Wavelet-based Method for Classification of Meningioma Histology Images

Qureshi H, Rajpoot N, Nattkemper TW, Hans V. A Robust Adaptive Wavelet-based Method for Classification of Meningioma Histology Images. In: MICCAI«2009 Workshop on Optical Tissue Image Analysis in Microscopy, Histology, and Endoscopy. 2009.Intra-class variability in the texture of samples is an im- portant problem in the domain of histological image classi?cation. This issue is inherent to the ?eld due to the high complexity of histology im- age data. A technique that provides good results in one trial may fail in another when the test and training data are changed and therefore, the technique needs to be adapted for intra-class texture variation. In this paper, we present a novel wavelet based multiresolution analysis approach to meningioma subtype classi?cation in response to the chal- lenge of data variation. We analyze the stability of Adaptive Discriminant Wavelet Packet Transform (ADWPT) and present a solution to the issue of variation in the ADWPT decomposition when texture in data changes. A feature selection approach is proposed that provides high classi?cation accuracy