Brain Tumor Segmentation Using Convolutional Neural Networks
Satyam Mittal, Tanya Gupta, Prof. Rohini khalkar
Tumor detection, Neural Networks
Tumor detection and removal is one medical issue that still remains challenging in the field of biomedicine. Early imaging techniques such as pneumoencephalography and cerebral angiography had the drawback of being invasive and hence the CT and MRI imaging techniques help the surgeons in providing a better vision. In this paper, tumor image processing involves three stages namely pre-processing, segmentation and morphological operation. After the acquisition of the source image, it is pre-processed by converting the original image to gray scale and median filter for quality enhancement is provided which is followed by enhancement stage resulting with historgramic equivalent image. Finally segmentation is done by means of morphological operation. The above proposed methodology is helpful in generating the reports automatically in less span of time and advancement has resulted in extracting many inferior parameters of the tumor.