Deep neural networks are known for their impressive performance in object detection and classification in "images in the wild" (images obtained using a simple internet search). However, only limited success has been observed in bio-medical images, especially those obtained from Magnetic Resonance Imaging (MRI) scans. Presenting a framework for classification and regression problems in bio-medical images. My approach extends the popular U-deep nets to facilitate learning using an induced region of interest extraction.
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ashkush/Diabetic-Retinopathy
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