Deep learning for enhanced brain Tumor Detection and classification

The purpose of this research is to build an automated, robust, intelligent and hybrid system for the early diagnosis and classifying of brain tumor. To serve this purpose, the authors propose the Auto Contrast Enhancer, Tumor Detector and Classifier to efficiently provide on-demand contrast improvement of poor contrast MRI images for the early diagnosis and classification of brain tumors. The classifier accomplishes its task through a two-phase approach. During the initial phase, ODTWCHE is employed to enhance image contrast, facilitating accurate diagnosis of brain tumours. In the subsequent phase, the classifier leverages the power of deep transfer learning, utilizing the pre-trained Inception V3 model to…

• NI
  National Institutes of Health