Deep learning for cardiac computer-aided diagnosis: benefits, issues & solutions

Deep Learning based Computer Aided Diagnosis System for Breast Mammograms

In this paper, a framework has been presented by using a combination of deep Convolutional Neural Network (CNN) with Support Vector Machine (SVM). Proposed method first perform preprocessing to resize the image so that it can be suitable for CNN and perform enhancement quality of the images can be enhanced. Deep Convolutional Neural Network (CNN) has been used for features extraction and classi...

Multiple Instance Learning for Computer Aided Diagnosis

Many computer aided diagnosis (CAD) problems can be best modelled as a multiple-instance learning (MIL) problem with unbalanced data: i.e. , the training data typically consists of a few positive bags, and a very large number of negative instances. Existing MIL algorithms are much too computationally expensive for these datasets. We describe CH, a framework for learning a Convex Hull representa...

Deep sparse feature selection for computer aided endoscopy diagnosis

In this paper, we develop a computer aided diagnosis algorithm to detect and classify the abnormalities in vision-based endoscopic examination. We focus on analyzing the traditional gastroscope data and help the medical experts improve the accuracy of medical diagnosis with our analysis tool. To achieve this, we first segment the image into superpixels, then extract various color and texture fe...

Fpga System for Computer-aided Diagnosis of Cardiac Murmurs

Master of Electrical Engineering Program School of Electrical and Computer Engineering

Deep Learning and Computer-Aided Diagnosis for Medical Image Processing: A Personal Perspective