Anushka ShendkarShruti YadavMayuri PuseNikita RakhProf. Revati Patil
In this paper, we propose a brain tumor segmentation and classification method for multi-modality magnetic resonance image scans. The data from multi-modal brain tumor segmentation challenge are utilized which are co-registered and skull stripped, and the histogram matching is performed with a reference volume of high contrast. We are detecting tumor by using preprocessing , segmentation, feature extraction ,optimization and lastly classification after that preprocessed images use to classify the tissue .We performed a leave-one out cross-validation and achieved 88 Dice overlap for the complete tumor region, 75 for the core tumor region and 95 for enhancing tumor region, which is higher than the Dice overlap reported.
P. NagarajV. MuneeswaranL. Veera ReddyParvathaneni UpendraM. Vishnu Vardhan Reddy
Hossam H. SultanNancy M. SalemWalid Al‐Atabany
Pramit DuttaKhaleda Akhter SathiMd. Saiful Islam
Gökalp ÇınarerBülent Gürsel EmiroğluRecep Sinan ArslanAhmet Haşim Yurttakal