Magnetic Resonance Imaging (MRI) is a widely-used technique for clinics. Its advantages in providing multiple complimentary contrasts make it the best image tool for detecting presenting lesions in the brain. A lot methods have been proposed for lesion detection and segmentations using machine learning techniques. It is more sophisticated than common computer vision tasks since the estimation of treatment outcomes are not merely determined by lesions captured by current MR images. We targeted to develop an algorithm, based on 3D Convolutional Neural Network, to predict the final lesion shown on day-90 scans by processing the day-0 acute stroke images.
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