Paper Info
Title
Selective Search and Sequential Detection for Standard Plane Localization in Ultrasound.
Abstract
We present the first automatic solution for localizing fetal abdominal standard plane (FASP) in consecutive 2D ultrasound images. FASP is located in the presence of three key anatomies detected by learning based algorithms, including stomach bubble (SB), umbilical vein (UV), and spine (SP). Traditional detection methods exhaustively scanning the entire image with sliding window algorithms tend not to perform well, since large numbers of regions appear similar to key anatomies. We propose a novel approach by applying local detectors sequentially on the preselected locations of SB, SP and UV. Specifically, we employ segmentation to generate probable locations for SB detection while exploiting a novel accumulative vessel probability algorithm to produce probable locations for SP and UV detection. The sequential scheme automatically excludes detected regions in former steps for subsequent detection, and further limits the search range according to the geometric relationship among anatomies. Experimental results on 100 fetal abdomen videos show that our method significantly outperforms traditional methods that only use local detector. © 2013 Springer-Verlag.
Year
DOI
Venue
2013
10.1007/978-3-642-41083-3_23
Abdominal imaging
Keywords
Field
DocType
IMAGES
Fetal abdomen,Computer vision,Sliding window protocol,AdaBoost,Segmentation,Artificial intelligence,Radiology,Detector,Medicine,Ultrasound
Conference
Volume
Issue
ISSN
8198 LNCS
null
16113349
Citations 
PageRank 
References 
7
0.63
7
Authors
9
Name
Order
Citations
PageRank
Dong Ni136737.37
Tianmei Li270.63
Xin Yang3799.59
Jing Qin470.97
Shengli Li518418.06
Chien Ting Chin6282.16
Shuyuan Ouyang7101.02
Tianfu Wang838255.46
Si-Ping Chen926537.25