TY - GEN
T1 - Calcium removal from cardiac ct images using deep convolutional neural network
AU - Yan, Siming
AU - Shi, Feng
AU - Chen, Yuhua
AU - Dey, Damini
AU - Lee, Sang Eun
AU - Chang, Hyuk Jae
AU - Li, Debiao
AU - Xie, Yibin
N1 - Publisher Copyright:
© 2018 IEEE.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/5/23
Y1 - 2018/5/23
N2 - Coronary calcium causes beam hardening and blooming artifacts on cardiac computed tomography angiography (CTA) images, which lead to overestimation of lumen stenosis and reduction of diagnostic specificity. To properly remove coronary calcification and restore arterial lumen precisely, we propose a machine learning-based method with a multi-step inpainting process. We developed a new network configuration, Dense-Unet, to achieve optimal performance with low computational cost. Results after the calcium removal process were validated by comparing with gold-standard X-ray angiography. Our results demonstrated that removing coronary calcification from images with the proposed approach was feasible, and may potentially improve the diagnostic accuracy of CTA.
AB - Coronary calcium causes beam hardening and blooming artifacts on cardiac computed tomography angiography (CTA) images, which lead to overestimation of lumen stenosis and reduction of diagnostic specificity. To properly remove coronary calcification and restore arterial lumen precisely, we propose a machine learning-based method with a multi-step inpainting process. We developed a new network configuration, Dense-Unet, to achieve optimal performance with low computational cost. Results after the calcium removal process were validated by comparing with gold-standard X-ray angiography. Our results demonstrated that removing coronary calcification from images with the proposed approach was feasible, and may potentially improve the diagnostic accuracy of CTA.
UR - http://www.scopus.com/inward/record.url?scp=85048119567&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85048119567&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2018.8363617
DO - 10.1109/ISBI.2018.8363617
M3 - Conference contribution
AN - SCOPUS:85048119567
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 466
EP - 469
BT - 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018
PB - IEEE Computer Society
T2 - 15th IEEE International Symposium on Biomedical Imaging, ISBI 2018
Y2 - 4 April 2018 through 7 April 2018
ER -