000201868 001__ 201868
000201868 005__ 20180913062704.0
000201868 0247_ $$2doi$$a10.1007/978-3-319-16220-1_26
000201868 020__ $$a978-3-319-16220-1
000201868 020__ $$a978-3-319-16219-5
000201868 02470 $$2ISI$$a000361842800026
000201868 037__ $$aCONF
000201868 245__ $$aRefining Mitochondria Segmentation in Electron Microscopy Imagery with Active Surfaces
000201868 269__ $$a2014
000201868 260__ $$aBerlin$$bSpringer$$c2014
000201868 336__ $$aConference Papers
000201868 490__ $$aLecture Notes in Computer Science$$v8928
000201868 520__ $$aWe present an active surface-based method for refining the boundary surfaces of mitochondria segmentation data. We exploit the fact that mitochondria have thick dark membranes, so referencing the image data at the inner membrane can help drive a more accurate delineation of the outer membrane surface. Given the initial boundary prediction from a machine learning-based segmentation algorithm as input, we compare several cost functions used to drive an explicit update scheme to locally refine 3D mesh surfaces, and results are presented on electron microscopy imagery. Our resulting surfaces are seen to fit very accurately to the mitochondria membranes, more accurately even than the available hand-annotations of the data.
000201868 700__ $$aJorstad, Anne
000201868 700__ $$0240252$$aFua, Pascal$$g112366
000201868 7112_ $$aEuropean Conference on Computer Vision (ECCV) Workshop on Non-Rigid Shape Analysis and Deformable Image Alignment$$cZurich, Switzerland$$dSeptember 6-12, 2014
000201868 720_1 $$aAgapito, Lourdes$$eed.
000201868 720_1 $$aBronstein, Michael M.$$eed.
000201868 720_1 $$aRother, Carsten$$eed.
000201868 773__ $$jIV$$q367-379$$tComputer Vision - ECCV 2014 Workshops
000201868 8564_ $$s1947181$$uhttps://infoscience.epfl.ch/record/201868/files/JorstadECCV2014.pdf$$yPostprint$$zPostprint
000201868 909C0 $$0252087$$pCVLAB$$xU10659
000201868 909CO $$ooai:infoscience.tind.io:201868$$pconf$$pIC
000201868 917Z8 $$x225441
000201868 917Z8 $$x148230
000201868 937__ $$aEPFL-CONF-201868
000201868 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000201868 980__ $$aCONF