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Computer aided insights on obscure cases of breast cancer diagnosis

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dc.contributor.author Andreadis, I en
dc.contributor.author Nikita, K en
dc.contributor.author Giannakopoulou, G en
dc.contributor.author Koulocheri, D en
dc.contributor.author Zografos, G en
dc.contributor.author Antaraki, A en
dc.contributor.author Ligomenides, P en
dc.contributor.author Spyrou, G en
dc.date.accessioned 2014-03-01T02:45:12Z
dc.date.available 2014-03-01T02:45:12Z
dc.date.issued 2008 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/32196
dc.subject BI-RADS en
dc.subject Breast cancer en
dc.subject CAD en
dc.subject Microcalcifications en
dc.subject.other Classifiers en
dc.subject.other Computer aided analysis en
dc.subject.other Computer aided diagnosis en
dc.subject.other Diagnosis en
dc.subject.other Diagnostic radiography en
dc.subject.other Digital image storage en
dc.subject.other Imaging systems en
dc.subject.other Learning systems en
dc.subject.other Mammography en
dc.subject.other Medical imaging en
dc.subject.other Optoelectronic devices en
dc.subject.other Technical presentations en
dc.subject.other Analysis and evaluations en
dc.subject.other BI-RADS en
dc.subject.other Breast cancer en
dc.subject.other Breast cancer diagnoses en
dc.subject.other CAD en
dc.subject.other Cad systems en
dc.subject.other Classification results en
dc.subject.other Clustered microcalcifications en
dc.subject.other Evaluation results en
dc.subject.other Hippocrates en
dc.subject.other Hybrid classifiers en
dc.subject.other Microcalcifications en
dc.subject.other Calcification (biochemistry) en
dc.title Computer aided insights on obscure cases of breast cancer diagnosis en
heal.type conferenceItem en
heal.identifier.primary 10.1109/IST.2008.4659976 en
heal.identifier.secondary http://dx.doi.org/10.1109/IST.2008.4659976 en
heal.identifier.secondary 4659976 en
heal.publicationDate 2008 en
heal.abstract Breast cancer is a leading cause of deaths in women. Mammography is considered as the most effective technology presently available for breast cancer screening, being very effective in the detection of clustered microcalcifications which are considered as one of the most important findings associated to the existence of breast cancer. A computer aided diagnosis (CAD) system named ""Hippocrates-mst"" has been already developed in the lab based on detailed analysis and evaluation of related features of microcalcifications (individually and in clusters). Preliminary evaluation results have shown that the system achieves high levels of sensitivity, while suffering from low specificity. For this reason, our current studies aim to a methodology refinement which will lead to optimized classification results. In this paper, we focus on obscure diagnostic cases classified by the radiologists as BI-RADS 3. In such cases, although short-term re-examination is normally advised, radiologists and physicians usually have strong doubts about their recommendations. We tested the performance of two classifiers embedded in the proposed CAD system using a dataset of 63 (57 benign and 6 malignant) mammograms, all classified as BI-RADS 3 and biopsy proven. The sensitivity achieved by the first one (the default Hippocrates-mst classifier) is as high as 100%, classifying correctly all the malignant cases. As far as the benign cases are concerned, system's specificity is 35.09%. Using the second classifier (a rule based and SVM hybrid classifier) the specificity increases to 63.16% with a cost of sensitivity decrease to 66.67%. ©2008 IEEE. en
heal.journalName IST 2008 - IEEE Workshop on Imaging Systems and Techniques Proceedings en
dc.identifier.doi 10.1109/IST.2008.4659976 en
dc.identifier.spage 237 en
dc.identifier.epage 241 en


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