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A Cascade Classifier for Diagnosis of Melanoma in Clinical Images
Auckland University of Technology, New Zealand.
Auckland University of Technology, New Zealand.
Mälardalens högskola, Akademin för innovation, design och teknik, Inbyggda system.ORCID-id: 0000-0002-1550-0994
Auckland University of Technology, New Zealand.
2014 (Engelska)Ingår i: The 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE EMBC14, 2014, s. 6748-6751Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Computer aided diagnosis of medical images can help physicians in better detecting and early diagnosis of many symptoms and therefore reducing the mortality rate. Realization of an efficient mobile device for semi-automatic diagnosis of melanoma would greatly enhance the applicability of medical image classification scheme and make it useful in clinical contexts. In this paper, interactive object recognition methodology is adopted for border segmentation of clinical skin lesion images. In addition, performance of five classifiers, KNN, Naïve Bayes, multi-layer perceptron, random forest and SVM are compared based on color and texture features for discriminating melanoma from benign nevus. The results show that a sensitivity of 82.6% and specificity of 83% can be achieved using a single SVM classifier. However, a better classification performance was achieved using a proposed cascade classifier with the sensitivity of 83.06% and specificity of 90.05% when performing ten-fold cross validation.

Ort, förlag, år, upplaga, sidor
2014. s. 6748-6751
Nationell ämneskategori
Elektroteknik och elektronik
Identifikatorer
URN: urn:nbn:se:mdh:diva-26781DOI: 10.1109/EMBC.2014.6945177Scopus ID: 2-s2.0-84929494210ISBN: 978-1-4244-7929-0 (tryckt)OAI: oai:DiVA.org:mdh-26781DiVA, id: diva2:768558
Konferens
The 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society IEEE EMBC14, 26 Aug 2014, Chicago, United States
Projekt
RALF3 - Software for Embedded High Performance ArchitecturesTillgänglig från: 2014-12-04 Skapad: 2014-12-02 Senast uppdaterad: 2018-02-22Bibliografiskt granskad

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Larsson, Thomas B

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