A new smart probe system for a tablet PC-based point-of-care ultrasound imaging system: Feasibility study

2014 ◽  
Author(s):  
Yeongnam Lee ◽  
Jeeun Kang ◽  
Sunmi Yeo ◽  
Jaejin Lee ◽  
Gi-Duck Kim ◽  
...  
Keyword(s):  
Ultrasound Imaging ◽  
Feasibility Study ◽  
Imaging System ◽  
Point Of Care ◽  
Point Of Care Ultrasound ◽  
Tablet Pc ◽  
Probe System

scholarly journals Reverse Scan Conversion and Efficient Deep Learning Network Architecture for Ultrasound Imaging on a Mobile Device

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2629
Author(s):  
Kunkyu Lee ◽  
Min Kim ◽  
Changhyun Lim ◽  
Tai-Kyong Song
Keyword(s):  
Deep Learning ◽  
Ultrasound Imaging ◽  
Mobile Device ◽  
Network Architecture ◽  
Point Of Care ◽  
Ultrasound Image ◽  
Training Dataset ◽  
Point Of Care Ultrasound ◽  
Reverse Scan ◽  
Scan Conversion

Point-of-care ultrasound (POCUS), realized by recent developments in portable ultrasound imaging systems for prompt diagnosis and treatment, has become a major tool in accidents or emergencies. Concomitantly, the number of untrained/unskilled staff not familiar with the operation of the ultrasound system for diagnosis is increasing. By providing an imaging guide to assist clinical decisions and support diagnosis, the risk brought by inexperienced users can be managed. Recently, deep learning has been employed to guide users in ultrasound scanning and diagnosis. However, in a cloud-based ultrasonic artificial intelligence system, the use of POCUS is limited due to information security, network integrity, and significant energy consumption. To address this, we propose (1) a structure that simultaneously provides ultrasound imaging and a mobile device-based ultrasound image guide using deep learning, and (2) a reverse scan conversion (RSC) method for building an ultrasound training dataset to increase the accuracy of the deep learning model. Experimental results show that the proposed structure can achieve ultrasound imaging and deep learning simultaneously at a maximum rate of 42.9 frames per second, and that the RSC method improves the image classification accuracy by more than 3%.

Acute Orthodeoxia: Evaluation Using Point-of-Care Ultrasound Imaging

2017 ◽  
Vol 14 (4) ◽  
pp. 594-596 ◽  
Author(s):  
Rishik Vashisht ◽  
Siddharth Dugar ◽  
Narendrakumar Alappan ◽  
Ajit Moghekar
Keyword(s):  
Ultrasound Imaging ◽  
Point Of Care ◽  
Point Of Care Ultrasound

scholarly journals Feasibility Study of Improved Patch Group Prior Based Denoising (PGPD) Technique with Medical Ultrasound Imaging System

2017 ◽  
Vol 22 (1) ◽  
pp. 55-59 ◽  
Author(s):  
Seung Hun Kim ◽  
Kanghyen Seo ◽  
Seong Hyeon Kang ◽  
Jong Hun Kim ◽  
Won Ho Choi ◽  
...  
Keyword(s):  
Ultrasound Imaging ◽  
Feasibility Study ◽  
Imaging System ◽  
Medical Ultrasound ◽  
Medical Ultrasound Imaging ◽  
Patch Group
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