Paper Info
Title
Automatic corpus callosum segmentation for standardized MR brain scanning
Abstract
Magnetic Resonance (MR) brain scanning is often planned manually with the goal of aligning the imaging plane with key anatomic landmarks. The planning is time-consuming and subject to inter- and intra- operator variability. An automatic and standardized planning of brain scans is highly useful for clinical applications, and for maximum utility should work on patients of all ages. In this study, we propose a method for fully automatic planning that utilizes the landmarks from two orthogonal images to define the geometry of the third scanning plane. The corpus callosum (CC) is segmented in sagittal images by an active shape model (ASM), and the result is further improved by weighting the boundary movement with confidence scores and incorporating region based refinement. Based on the extracted contour of the CC, several important landmarks are located and then combined with landmarks from the coronal or transverse plane to define the geometry of the third plane. Our automatic method is tested on 54 MR images from 24 patients and 3 healthy volunteers, with ages ranging from 4 months to 70 years old. The average accuracy with respect to two manually labeled points on the CC is 3.54 mm and 4.19 mm, and differed by an average of 2.48 degrees from the orientation of the line connecting them, demonstrating that our method is sufficiently accurate for clinical use.
Year
DOI
Venue
2007
10.1117/12.710090
PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)
Keywords
Field
DocType
segmentation,shape,automatic planning of scan
Computer vision,Active shape model,Coronal plane,Transverse plane,Segmentation,Computer science,Artificial intelligence,Neuroimaging,Corpus callosum,Sagittal plane,Magnetic resonance imaging
Conference
Volume
ISSN
Citations 
6512
0277-786X
1
PageRank 
References 
Authors
0.36
0
4
Name
Order
Citations
PageRank
Qing Xu12014.16
hong chen211.04
Li Zhang3235.03
Carol L. Novak414623.88