Using Autoencoders to Reduce Dimensionality of DICOM Metadata
Author:
Affiliation:
1. University of Rijeka,Faculty of Engineering,Rijeka,Croatia,51000
2. University of Rijeka, Clinical Hospital Centre Rijeka,Rijeka,Croatia,51000
3. Medical University of Graz,Graz,Austria,8036
Funder
Croatian Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9987724/9987729/09988310.pdf?arnumber=9988310
Reference21 articles.
1. Using DICOM Tags for Clustering Medical Radiology Images into Visually Similar Groups
2. Human embryonic stem cell classification: random network with autoencoded feature extractor
3. Predicting the fidelity of JPEG2000 compressed CT images using DICOM header information
4. Quality of DICOM header information for image catego-rization;guld;Proceedings of SPIE - The International Society for Optical Engineering,2002
5. Deep Learning using Rectified Linear Units (ReLU);agarap;CoRR vol abs/1803 08375,2018
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