Hello World Deep Learning in Medical Imaging

By P. Lakhani, Daniel L. Gray, Carl R. Pett, P. Nagy, G. Shih. 2018

102 citations recorded by the source corpus.

There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries to simplify their use. In this tutorial, we provide a high-level overview of how to build a deep neural network for medical image classification, and provide code that can help those new to the field begin their informatics projects.

Subfields: Artificial Intelligence, Radiology, Nuclear Medicine and Imaging

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In Artificial Intelligence

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

An overview of deep learning in medical imaging focusing on MRI (2018, methodology): “For example [130], with accompanying code available at https://github.”
A Gentle Introduction to Deep Learning in Medical Image Processing (2018, background): “tutorials and reviews [9, 10, 11, 12, 13, 14, 15, 16, 17, 18] over blog posts and jupyter notebooks [19, 20, 21] to entire books [22, 23].”