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		<citationkey>MirandaBarrSoarFeli:2012:StAnHi</citationkey>
		<title>Structural Analysis of Histological Images to Aid Diagnosis of Cervical Cancer</title>
		<format>DVD, On-line.</format>
		<year>2012</year>
		<numberoffiles>1</numberoffiles>
		<size>1678 KiB</size>
		<author>Miranda, Gisele Helena Barboni,</author>
		<author>Barrera, Junior,</author>
		<author>Soares, Edson Garcia,</author>
		<author>Felipe, Joaquim Cezar,</author>
		<affiliation>Department of Computing and Mathematics, Faculty of Philosophy, Sciences and Languages of Ribeirão Preto, USP</affiliation>
		<affiliation>Department of Computer Science, Institute of Mathematics and Statistics, USP</affiliation>
		<affiliation>Department of Pathology, Faculty of Medicine of Ribeirão Preto, USP</affiliation>
		<affiliation>Department of Computing and Mathematics, Faculty of Philosophy, Sciences and Languages of Ribeirão Preto, USP</affiliation>
		<editor>Freitas, Carla Maria Dal Sasso,</editor>
		<editor>Sarkar, Sudeep,</editor>
		<editor>Scopigno, Roberto,</editor>
		<editor>Silva, Luciano,</editor>
		<e-mailaddress>gisele.hbm@gmail.com</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 25 (SIBGRAPI)</conferencename>
		<conferencelocation>Ouro Preto</conferencelocation>
		<date>Aug. 22-25, 2012</date>
		<booktitle>Proceedings</booktitle>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<contenttype>External Contribution</contenttype>
		<keywords>Cervical Intraepithelial Neoplasia (CIN), neighborhood graphs, medical image processing, computer-aided diagnosis.</keywords>
		<abstract>The use of computational techniques in the processing of histopathological images allows the study of the structural organization of tissues and their pathological changes. The overall objective of this work includes the proposal, the implementation and the evaluation of a methodology for the analysis of cervical intraepithelial neoplasia (CIN) from histopathological images. For this pourpose, a pipeline of morphological operators were implemented for the segmentation of cell nuclei and the Delaunay Triangulation were used in order to represent the tissue architecture. Also, clustering algorithms and graph morphology were used to automatically obtain the boundary between the histological layers of the epithelial tissue. Similarity criteria and adjacency relations between the triangles of the network were explored. The proposed method was evaluated concerning the detection of the presence of lesions in the tissue as well as the their malignancy grading.</abstract>
		<language>en</language>
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