000205156 001__ 205156
000205156 005__ 20190812205825.0
000205156 037__ $$aCONF
000205156 245__ $$aIntensity-Based Point-Spread-Function-Aware Registration for Multi-View Applications in Optical Microscopy
000205156 269__ $$a2015
000205156 260__ $$c2015
000205156 336__ $$aConference Papers
000205156 520__ $$aWe present an algorithm to spatially register two volumetric datasets related via a rigid-body transform and degraded by an anisotropic point-spread-function (PSF). Registration is necessary, for example, when fusing data in multi-view microscopy. Automatic algorithms that only rely on maximizing pixel similarity, without accounting for the anisotropic image formation process, provide poor results in such applications. We propose to solve this problem by re-blurring the reference and test data with transformed forms of the PSF, in order to make them comparable, before minimizing the mean squared intensity difference between them. Our approach extends the pyramid-based sub-pixel registration algorithm proposed by Thévenaz et al., 1998, that employs an improved form of the Marquardt-Levenberg algorithm. We show, via simulations, that our method is more accurate than the conventional approach that does not account for the PSF. We demonstrate our algorithm in practice by registering multi-view volumes of a zebrafish larva acquired using a wide-field microscope.
000205156 6531_ $$aFluorescence Microscopy
000205156 6531_ $$aFluorescence tomography
000205156 6531_ $$aImage registration
000205156 700__ $$aChacko, Nikhil
000205156 700__ $$aChan, Kevin G.
000205156 700__ $$aLiebling, Michael
000205156 7112_ $$aBiomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
000205156 909C0 $$xU10381$$pLIDIAP$$0252189
000205156 909CO $$pconf$$pSTI$$ooai:infoscience.tind.io:205156
000205156 937__ $$aEPFL-CONF-205156
000205156 970__ $$aChacko_ISBI15_2015/LIDIAP
000205156 973__ $$aEPFL
000205156 980__ $$aCONF