Medical Imaging Diagnosis Assistant

The goal of this project is to propose a new methodology for fully automated breast cancer detection and segmentation from multi-modal medical images introducing clinical covariates. This protocol provides the following novelties. First, it lies on the use of deep convolutional neural networks (CNNs) that will incorporate several image modalities: 3D magnetic resonance images (MRI), ultrasound (US) or Mammography (MG) views. This is the first methodology that is able to classify a whole exam, containing all the above image modalities.

In this project, we are interested to develop a new assistant (i.e. a system that will provide diagnosis support as a second opinion), for other human tissues, besides the breast. This will embrace other anatomies such as the aorta, spinal column, epicardial fat, body fat, heart, lungs, and muscle.