Segmenting Brain Metastases Using Deep Learning on Multi-Modal MRI

Detecting and segmenting brain metastases is a tedious and time-consuming task for many radiologists, particularly with the growing use of multi-modal 3D imaging. Using deep learning to learn from the comprehensive pixel-wise labeled MRI-data, this work aims to train a fully convolution neural network for automatic detection and segmentation of brain metastases using multi-modal MRI. By training and testing on over 100 and 50 patients, respectively, including a variety of size and number of brain metastases from several primary cancers, this work provides a comprehensive investigation on the value and potential use of machine learning in a clinically relevant setting.