SPAER: Sparse Deep Convolutional Autoencoder Model to Extract Low Dimensional Imaging Biomarkers for Early Detection of Breast Cancer Using Dynamic Thermography

SPAER: Sparse Deep Convolutional Autoencoder Model to Extract Low Dimensional Imaging Biomarkers for Early Detection of Breast Cancer Using Dynamic Thermography

Early diagnosis of breast cancer unequivocally improves the survival rate of patients and is crucial for disease treatment. With the current developments in infrared imaging, breast screening using dynamic thermography seems to be a great complementary method for clinical breast examination (CBE) pr...

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Bibliographic Details
Main Authors: Bardia Yousefi, Hamed Akbari, Michelle Hershman, Satoru Kawakita, Henrique C. Fernandes, Clemente Ibarra-Castanedo, Samad Ahadian, Xavier P. V. Maldague
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Applied Sciences
Subjects:
breast cancer
thermography
sparse deep convolutional autoencoder
matrix factorization
dimensionality reduction
thermomics
Online Access:https://www.mdpi.com/2076-3417/11/7/3248

Internet

https://www.mdpi.com/2076-3417/11/7/3248

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