Development of an integrated breast tissue density classification software system

Chatzistergos, S; Stoitsis, J; Nikita, KS; Papaevangelou, A

dc.contributor.author	Chatzistergos, S	en
dc.contributor.author	Stoitsis, J	en
dc.contributor.author	Nikita, KS	en
dc.contributor.author	Papaevangelou, A	en
dc.date.accessioned	2014-03-01T02:45:14Z
dc.date.available	2014-03-01T02:45:14Z
dc.date.issued	2008	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32221
dc.subject	Anisotropic filtering	en
dc.subject	BIRADS	en
dc.subject	Breast density	en
dc.subject	Computer aided diagnosis	en
dc.subject	Gabor wavelets	en
dc.subject	Mammograms	en
dc.subject	Medical image processing and analysis	en
dc.subject	Monogenic signal	en
dc.subject	pLSA	en
dc.subject	Texture analysis	en
dc.subject.other	Anisotropy	en
dc.subject.other	Computer aided analysis	en
dc.subject.other	Computer software	en
dc.subject.other	Digital image storage	en
dc.subject.other	Image processing	en
dc.subject.other	Imaging systems	en
dc.subject.other	Information theory	en
dc.subject.other	Medical imaging	en
dc.subject.other	Muscle	en
dc.subject.other	Optoelectronic devices	en
dc.subject.other	Technical presentations	en
dc.subject.other	Textures	en
dc.subject.other	Anisotropic filtering	en
dc.subject.other	BIRADS	en
dc.subject.other	Breast density	en
dc.subject.other	Gabor wavelets	en
dc.subject.other	Mammograms	en
dc.subject.other	Medical image processing and analysis	en
dc.subject.other	Monogenic signal	en
dc.subject.other	pLSA	en
dc.subject.other	Texture analysis	en
dc.subject.other	Computer aided diagnosis	en
dc.title	Development of an integrated breast tissue density classification software system	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/IST.2008.4659977	en
heal.identifier.secondary	http://dx.doi.org/10.1109/IST.2008.4659977	en
heal.identifier.secondary	4659977	en
heal.publicationDate	2008	en
heal.abstract	The current work aims at the classification of breast tissue according to Breast Imaging Reporting and Data System (BIRADS), based on texture features from mammographic images. To this end an integrated software system was developed in visual C++ using the .NET 2.0 Framework. The system takes as inputs pictures in most of the popular bitmap formats as well as DICOM and provides as output a specific breast density category according to the BIRADS system. The functionality of the system is provided by three modules: (a) the pre-processing module, where a set of tools for image manipulation (rotation, crop, gray level adjustment) are available accompanied by the ability to perform anisotropic filtering to the input image, (b) the breast segmentation module where the breast region is separated from the image background and pectoral muscle using characteristics of monogenic signals and Gabor wavelets respectively and (c) the breast tissue density classification module where the breast tissue is categorized according to the BIRADS, using texture characteristics and probabilistic Latent Semantic Analysis (PLSA). Special emphasis has been given to the development of a functional and user-friendly interface. ©2008 IEEE.	en
heal.journalName	IST 2008 - IEEE Workshop on Imaging Systems and Techniques Proceedings	en
dc.identifier.doi	10.1109/IST.2008.4659977	en
dc.identifier.spage	243	en
dc.identifier.epage	245	en