000000676 001__ 676
000000676 005__ 20190611210123.0
000000676 037__ $$aCONFERENCE
000000676 041__ $$aeng
000000676 245__ $$aTexture classification of anatomical structures using a context-free machine learning approach
000000676 260__ $$c2015$$b21-26 February$$aOrlando, USA
000000676 269__ $$a2015-02
000000676 300__ $$a14 p.
000000676 506__ $$avisible
000000676 520__ $$aMedical images contain a large amount of visual information about structures and anomalies in the human body. To make sense of this information, human interpretation is often essential. On the other hand, computer-based approaches can exploit information contained in the images by numerically measuring and quantifying specic visual features. Annotation of organs and other anatomical regions is an important step before computing numerical features on medical images. In this paper, a texture-based organ classication algorithm is presented, which can be used to reduce the time required for annotating medical images. The texture of organs is analyzed using a combination of state{of{the{art techniques: the Riesz transform and a bag of meaningful visual words. The eect of a meaningfulness transformation in the visual word space yields two important advantages that can be seen in the results. The number of descriptors is enormously reduced down to 10% of the original size, whereas classication accuracy is improved by up to 25% with respect to the baseline approach.$$9eng
000000676 592__ $$aHEG-VS
000000676 592__ $$bInstitut Informatique de gestion
000000676 592__ $$cEconomie et Services
000000676 65017 $$aInformatique
000000676 655_7 $$afull paper
000000676 6531_ $$aorgan texture$$9eng
000000676 6531_ $$aRiesz wavelets$$9eng
000000676 6531_ $$acomputer{aided diagnosis$$9eng
000000676 700__ $$uUniversity of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) : University Hospitals and University of Geneva, Geneva, Switzerland$$aJimenez del Toro, Oscar Alfonso
000000676 700__ $$uSwiss Federal Institute of Technology (ETH) Zurich, Zurich, Switzerland$$aFoncubierta-Rodriguez, Antonio
000000676 700__ $$uUniversity of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) : University Hospitals and University of Geneva, Geneva, Switzerland$$aDepeursinge, Adrien
000000676 700__ $$aMüller, Henning$$uUniversity of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis) : University Hospitals and University of Geneva, Geneva, Switzerland
000000676 711__ $$aSPIE medical imaging$$cOrlando, USA$$d21/02/2015 / 26/02/2015
000000676 773__ $$tProceedings of SPIE medical imaging 2015
000000676 8564_ $$uhttps://hesso.tind.io/record/676/files/jimenez_textureclassification_2015.pdf$$s1911654
000000676 8560_ $$fmelissa.paez@hesge.ch
000000676 909CO $$pECONOMIESERVICES_CONFERENCE$$pDOMAINE_ECONOMIESERVICE_CONFERENCE$$pGLOBAL_SET$$ooai:hesso.tind.io:676
000000676 906__ $$aGREEN
000000676 950__ $$aI1
000000676 980__ $$aconference