Technology trends and applications of deep learning in ultrasonography: image quality enhancement, diagnostic support, and improving workflow efficiency
- Author:
Jonghyon YI
1
;
Ho Kyung KANG
;
Jae-Hyun KWON
;
Kang-Sik KIM
;
Moon Ho PARK
;
Yeong Kyeong SEONG
;
Dong Woo KIM
;
Byungeun AHN
;
Kilsu HA
;
Jinyong LEE
;
Zaegyoo HAH
;
Won-Chul BANG
Author Information
- Publication Type:17
- From: Ultrasonography 2021;40(1):7-22
- CountryRepublic of Korea
- Language:English
- Abstract: In this review of the most recent applications of deep learning to ultrasound imaging, the architectures of deep learning networks are briefly explained for the medical imaging applications of classification, detection, segmentation, and generation. Ultrasonography applications for image processing and diagnosis are then reviewed and summarized, along with some representative imaging studies of the breast, thyroid, heart, kidney, liver, and fetal head. Efforts towards workflow enhancement are also reviewed, with an emphasis on view recognition, scanning guide, image quality assessment, and quantification and measurement. Finally some future prospects are presented regarding image quality enhancement, diagnostic support, and improvements in workflow efficiency, along with remarks on hurdles, benefits, and necessary collaborations.
