Multi-scale directional-filtering-based method for follicular lymphoma grading

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buir.contributor.authorÇetin, A. Enis
buir.contributor.orcidÇetin, A. Enis|0000-0002-3449-1958
dc.citation.epage70en_US
dc.citation.issueNumberSupplement 1en_US
dc.citation.spage63en_US
dc.citation.volumeNumber8en_US
dc.contributor.authorBozkurt, A.en_US
dc.contributor.authorSuhre, A.en_US
dc.contributor.authorÇetin, A. Enisen_US
dc.date.accessioned2015-07-28T12:02:45Z
dc.date.available2015-07-28T12:02:45Z
dc.date.issued2014-08-07en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.description.abstractFollicular lymphoma (FL) is a group of malignancies of lymphocyte origin that arise from lymph nodes, spleen, and bone marrow in the lymphatic system. It is the second most common non-Hodgkins lymphoma. Characteristic of FL is the presence of follicle center B cells consisting of centrocytes and centroblasts. Typically, FL images are graded by an expert manually counting the centroblasts in an image. This is time consuming. In this paper, we present a novel multi-scale directional filtering scheme and utilize it to classify FL images into different grades. Instead of counting the centroblasts individually, we classify the texture formed by centroblasts. We apply our multi-scale directional filtering scheme in two scales and along eight orientations, and use the mean and the standard deviation of each filter output as feature parameters. For classification, we use support vector machines with the radial basis function kernel. We map the features into two dimensions using linear discriminant analysis prior to classification. Experimental results are presented.en_US
dc.description.provenanceMade available in DSpace on 2015-07-28T12:02:45Z (GMT). No. of bitstreams: 1 8323.pdf: 1758412 bytes, checksum: c39eee42123f2596e80bba4985bf372b (MD5)en
dc.identifier.doi10.1007/s11760-014-0681-0en_US
dc.identifier.issn1863-1703
dc.identifier.urihttp://hdl.handle.net/11693/12724
dc.language.isoEnglishen_US
dc.publisherSpringer U Ken_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s11760-014-0681-0en_US
dc.source.titleSignal, Image and Video Processingen_US
dc.subjectFollicular lymphomaen_US
dc.subjectDirectional filteringen_US
dc.subjectSVMen_US
dc.subjectTexture classificationen_US
dc.titleMulti-scale directional-filtering-based method for follicular lymphoma gradingen_US
dc.typeArticleen_US

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