Unsupervised Pathology Detection in Medical Images using Learning-based Methods-Reference-Cited by-同舟云学术

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Unsupervised Pathology Detection in Medical Images using Learning-based Methods

Published:2018 Issue: Volume: Page:61-66
ISSN:1431-472X
Container-title:Bildverarbeitung für die Medizin 2018
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Author:

Uzunova Hristina,Handels Heinz,Ehrhardt Jan

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-662-56537-7_30

Reference10 articles.

1. Kamnitsas K, Ferrante E, Parisot S, et al. DeepMedic for brain tumor segmentation. Proc MICCAI. 2016; p. 138–149.

2. Krüger J, Ehrhardt J, Handels H. Probabilistic appearance models for segmentation and classification. Proc ICCV. 2015; p. 1698–1706.

3. Schlegl T, Seeböck P, Waldstein SM, et al. Unsupervised anomaly detection with generative adversarial networks to guide marker discovery. Inf Process Med Imaging. 2017; p. 146–157.

4. Barnes C, Shechtman E, Finkelstein A, et al. PatchMatch: A randomized correspondence algorithm for structural image editing. Proc ACM SIGGRAPH. 2009;28(3).

5. Faktor A, Irani M. Clustering by composition: unsupervised discovery of image categories. Proc ECCV. 2012; p. 474–487.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep learning and radiomics in precision medicine;Expert Review of Precision Medicine and Drug Development;2019-03-04

2. Unsupervised pathology detection in medical images using conditional variational autoencoders;International Journal of Computer Assisted Radiology and Surgery;2018-12-12

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