Paper Info
Title
Real-Time Patient Table Removal In Ct Images
Abstract
As a routine tool for screening and examination, CT plays an important role in disease detection and diagnosis. Real-time table removal in CT images becomes a fundamental task to improve readability, interpretation and treatment planning. Meanwhile, it makes data management simple and benefits information sharing and communication in picture archiving and communication system. In this paper, we proposed an automated framework which utilized parallel programming to address this problem. Eight full-body CT images were collected and analyzed. Experimental results have shown that with parallel programming, the proposed framework can accelerate the patient table removal task up to three times faster when it was running on a personal computer with four-core central processing unit. Moreover, the segmentation accuracy reaches 99% of Dice coefficient. The idea behind this approach refreshes many algorithms for real-time medical image processing without extra hardware spending.
Year
DOI
Venue
2016
10.1007/978-3-319-48335-1_1
HEALTH INFORMATION SCIENCE, HIS 2016
Keywords
Field
DocType
Real-time, Parallel programming, Image segmentation, Health information science
Computer vision,Central processing unit,Segmentation,Picture archiving and communication system,Computer science,Sørensen–Dice coefficient,Personal computer,Image processing,Image segmentation,Artificial intelligence,Data management
Conference
Volume
ISSN
Citations 
10038
0302-9743
0
PageRank 
References 
Authors
0.34
6
6
Name
Order
Citations
PageRank
Luming Chen100.34
Shibin Wu221.47
Zhicheng Zhang3162.77
Shaode Yu4195.60
Yaoqin Xie512521.70
Hefang Zhang600.34