Linked Life Data

14654152

Source:http://linkedlifedata.com/resource/pubmed/id/14654152

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2003-12-5
pubmed:abstractText
Ovarian masses are a common phenomenon among women of all ages. The importance of prompt diagnosis of ovarian malignancies is obvious, due to the high mortality rate and the difficulty to detect a tumor in its early stages. In this work, an automatic technique for quantitative analysis and malignancy detection of ovarian masses using B-scan ultrasound (US) images is presented. The core of the technique is morphologic analysis of the ovarian mass. The method employed for this task is divided into two major stages: initial classification of the mass (into one of the three major tumor types: cyst, semisolid, solid), and detailed analysis of the mass. Malignancy evaluation is performed based on the collected data and the criteria provided by commonly used scoring systems. The results reflect adequate performance of the automatic method developed (referring to clinical requirements).
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0301-5629
pubmed:author
pubmed:issnType
Print
pubmed:volume
29
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1561-70
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
An automatic approach for morphological analysis and malignancy evaluation of ovarian masses using B-scans.
pubmed:affiliation
Medical Physics Department, Tel Aviv University, Tel Aviv, Israel.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't