Abstract
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.
Original language | English (US) |
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Pages (from-to) | 283-289 |
Number of pages | 7 |
Journal | Journal of Digital Imaging |
Volume | 31 |
Issue number | 3 |
DOIs | |
State | Published - Jun 1 2018 |
Keywords
- Artificial neural networks
- Deep learning
- Machine learning
- Medical imaging
ASJC Scopus subject areas
- Radiological and Ultrasound Technology
- Radiology Nuclear Medicine and imaging
- Computer Science Applications