Understanding the learned behavior of customized convolutional neural networks toward malaria parasite detection in thin blood smear images-Reference-Cited by-同舟云学术

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Understanding the learned behavior of customized convolutional neural networks toward malaria parasite detection in thin blood smear images

Published:2018-07-18 Issue:03 Volume:5 Page:1
ISSN:2329-4302
Container-title:Journal of Medical Imaging
language:
Short-container-title:J. Med. Imag.

Author:

Rajaraman Sivaramakrishnan¹,Silamut Kamolrat²,Hossain Md. A.³,Ersoy I.⁴,Maude Richard J.²,Jaeger Stefan¹,Thoma George R.¹,Antani Sameer K.¹

Affiliation:

1. Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, M

2. Mahidol University, Mahidol Oxford Tropical Medicine Research Unit, Bangkok

3. Chittagong Medical Hospital, Department of Medicine, Chittagong

4. University of Missouri, MU Informatics Institute, Department of Pathology and Anatomical Science, Co

Publisher

SPIE-Intl Soc Optical Eng

Subject

Radiology Nuclear Medicine and imaging

Reference44 articles.

1. Image analysis and machine learning for detecting malaria

2. Machine learning approach for automated screening of malaria parasite using light microscopic images

3. Automated image processing method for the diagnosis and classification of malaria on thin blood smears

4. The reliability of blood film examination for malaria at the peripheral health unit;Mitiku,2003

5. Deep learning

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