Linked Life Data

8309438

Source:http://linkedlifedata.com/resource/pubmed/id/8309438

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
1994-3-17
pubmed:abstractText
A computerized scheme for the automated detection of clustered microcalcifications from digital mammograms is being developed. This scheme is one part of an overall package for computer-aided diagnosis (CAD), the purpose of which is to assist radiologists in detecting and diagnosing breast cancer. One important step in the computer detection scheme is to group or cluster microcalcifications, since clustered microcalcifications are more clinically significant than are isolated microcalcifications. Previously a "growing" technique in which signals (possible microcalcifications) were clustered by grouping those that were within some predefined distance from the center of the growing cluster was used. In this paper, a new technique for grouping signals, which consists of two steps, is introduced. First, signals that may be several pixels in area are reduced to single pixels by means of a recursive transformation. Second, the number of signals (nonzero pixels) within a small region, typically 3.2 x 3.2 mm, are counted. Only if three or more signals are present within such a region are they preserved in the output image. In this way, isolated signals are eliminated. Furthermore, this method can eliminate falsely detected clusters, which were identified by a previous detection scheme, based on the spatial distribution of signals within the cluster. The differences in performance of the CAD scheme for detecting clustered microcalcifications using the old and new clustering techniques was measured using 78 mammograms, containing 41 clusters.(ABSTRACT TRUNCATED AT 250 WORDS)
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
0094-2405
pubmed:author
pubmed:issnType
Print
pubmed:volume
20
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1661-6
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:articleTitle
Computer-aided detection of clustered microcalcifications: an improved method for grouping detected signals.
pubmed:affiliation
Kurt Rossmann Laboratories for Radiologic Image Research, Department of Radiology, University of Chicago, Illinois 60637.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, Non-U.S. Gov't