Can I read Fast and Accurate Classification of Echocardiograms Using Deep Learning on EtoBox?

Fast and Accurate Classification of Echocardiograms Using Deep Learning by Madani, Ali; Arnaout, Ramy; Mofrad, Mohammad; Arnaout, Rima is a scholarly article available to read on EtoBox.

What is Fast and Accurate Classification of Echocardiograms Using Deep Learning about?

Echocardiography is essential to modern cardiology. However, human interpretation limits high throughput analysis, limiting echocardiography from reaching its full clinical and research potential for precision medicine. Deep learning is a cutting-edge machine-learning technique that has been useful in analyzing medical images but has not yet been widely applied to echocardiography, partly due to the complexity of echocardiograms' multi view, multi modality format. The essential first step toward comprehensive computer assisted echocardiographic interpretation is determining whether computers can learn to recognize standard views. To this end, we anonymized 834,267 transthoracic echocardiogram (TTE) images from 267 patients (20 to 96 years, 51 percent female, 26 percent obese) seen between 2000 and 2017 and labeled them according to standard views. Images covered a range of real world clinical variation. We built a multilayer convolutional neural network and used supervised learning to simultaneously classify 15 standard views. Eighty percent of data used was randomly chosen for training and 20 percent reserved for validation and testing on never seen echocardiograms. Using multiple

Author

Madani, Ali; Arnaout, Ramy; Mofrad, Mohammad; Arnaout, Rima

Published

2017

Language

EN