Linked Life Data

20142158

Source:http://linkedlifedata.com/resource/pubmed/id/20142158

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
5
pubmed:dateCreated
2010-7-27
pubmed:abstractText
Automatic prostate segmentation in transrectal ultrasound (TRUS) images is highly desired in many clinical applications. However, robust and automated prostate segmentation is challenging due to the low SNR in TRUS and the missing boundaries in shadow areas caused by calcifications or hyperdense prostate tissues. This paper presents a novel method of utilizing a priori shapes estimated from partial contours for segmenting the prostate. The proposed method is able to automatically extract prostate boundary from 2-D TRUS images without user interaction for shape correction in shadow areas. During the segmentation process, missing boundaries in shadow areas are estimated by using a partial active shape model, which takes partial contours as input but returns a complete shape estimation. With this shape guidance, an optimal search is performed by a discrete deformable model to minimize an energy functional for image segmentation, which is achieved efficiently by using dynamic programming. The segmentation of an image is executed in a multiresolution fashion from coarse to fine for robustness and computational efficiency. Promising segmentation results were demonstrated on 301 TRUS images grabbed from 19 patients with the average mean absolute distance error of 2.01 mm +/- 1.02 mm.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
May
pubmed:issn
1558-2531
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
57
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1158-66
pubmed:meshHeading
pubmed:year
2010
pubmed:articleTitle
Discrete deformable model guided by partial active shape model for TRUS image segmentation.
pubmed:affiliation
Philips Research North America, Briarcliff Manor, NY 10510, USA. pingkun.yan@philips.com
pubmed:publicationType
Journal Article