000145639 001__ 145639
000145639 005__ 20200925153944.0
000145639 037__ $$aDZNE-2020-00969
000145639 041__ $$aEnglish
000145639 1001_ $$0P:(DE-2719)2812477$$aConjeti, Sailesh$$b0$$udzne
000145639 1112_ $$aMICCAI 2018$$cGranada$$d2018-09-16 - 2018-09-16$$wSpain
000145639 245__ $$aInherent Brain Segmentation Quality Control from Fully ConvNet Monte Carlo Sampling
000145639 260__ $$c2018
000145639 3367_ $$033$$2EndNote$$aConference Paper
000145639 3367_ $$2DataCite$$aOther
000145639 3367_ $$2BibTeX$$aINPROCEEDINGS
000145639 3367_ $$2DRIVER$$aconferenceObject
000145639 3367_ $$2ORCID$$aLECTURE_SPEECH
000145639 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1597406708_15936$$xOther
000145639 520__ $$aWe introduce inherent measures for effective quality control of brain segmentation based on a Bayesian fully convolutional neural network, using model uncertainty. Monte Carlo samples from the posterior distribution are efficiently generated using dropout at test time. Based on these samples, we introduce next to a voxel-wise uncertainty map also three metrics for structure-wise uncertainty. We then incorporate these structure-wise uncertainty in group analyses as a measure of confidence in the observation. Our results show that the metrics are highly correlated to segmentation accuracy and therefore present an inherent measure of segmentation quality. Furthermore, group analysis with uncertainty results in effect sizes closer to that of manual annotations. The introduced uncertainty metrics can not only be very useful in translation to clinical practice but also provide automated quality control and group analyses in processing large data repositories.
000145639 536__ $$0G:(DE-HGF)POF3-345$$a345 - Population Studies and Genetics (POF3-345)$$cPOF3-345$$fPOF III$$x0
000145639 8564_ $$uhttps://www.springerprofessional.de/en/inherent-brain-segmentation-quality-control-from-fully-convnet-m/16122424
000145639 909CO $$ooai:pub.dzne.de:145639$$pVDB
000145639 9101_ $$0I:(DE-588)1065079516$$6P:(DE-2719)2812477$$aDeutsches Zentrum für Neurodegenerative Erkrankungen$$b0$$kDZNE
000145639 9131_ $$0G:(DE-HGF)POF3-345$$1G:(DE-HGF)POF3-340$$2G:(DE-HGF)POF3-300$$aDE-HGF$$bForschungsbereich Gesundheit$$lErkrankungen des Nervensystems$$vPopulation Studies and Genetics$$x0
000145639 9141_ $$y2018
000145639 9201_ $$0I:(DE-2719)1040310$$kAG Reuter$$lImage Analysis$$x0
000145639 980__ $$aconf
000145639 980__ $$aVDB
000145639 980__ $$aI:(DE-2719)1040310
000145639 980__ $$aUNRESTRICTED