A preview is not available for this record, please engage by choosing from the available options ‘download’ or ‘view’ to engage with the material
Description
Subhashis Banerjee This presentation introduces a new deep learning method for the automatic delineation and segmentation of brain tumors from multisequence magnetic resonance imaging (MRI). It includes a radiomic model to predict the overall survival based on the features extracted from the segmented volume of interest (VOI). Also included is an encoder-decoder-type convolutional neural network (ConvNet) model for pixel-wise segmentation of the tumor along three anatomical planes (axial, sagittal, and coronal) at the slice level.