PERFORM Publications

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Title		Authors	PubMed ID
1	Towards user-centered interactive medical image segmentation in VR with an assistive AI agent	Spiegler P; Harirpoush A; Xiao Y;	41509996 ENCS
2	MedCLIP-SAMv2: Towards universal text-driven medical image segmentation	Koleilat T; Asgariandehkordi H; Rivaz H; Xiao Y;	40779830 ENCS
3	Exploring interaction paradigms for segmenting medical images in virtual reality	Jones Z; Drouin S; Kersten-Oertel M;	40402355 ENCS
4	MRI as a viable alternative to CT for 3D surgical planning of Cavitary bone tumors	Chae Y; Cheers GM; Kim M; Reidler P; Klein A; Fevens T; Holzapfel BM; Mayer-Wagner S;	40049253 ENCS
5	Open access segmentations of intraoperative brain tumor ultrasound images	Behboodi B; Carton FX; Chabanas M; de Ribaupierre S; Solheim O; Munkvold BKR; Rivaz H; Xiao Y; Reinertsen I;	39047165 SOH
6	FishSegSSL: A Semi-Supervised Semantic Segmentation Framework for Fish-Eye Images	Paul S; Patterson Z; Bouguila N;	38535151 ENCS
7	Impaired performance of rapid grip in people with Parkinson's disease and motor segmentation	Rebecca J Daniels	38507858 PSYCHOLOGY
8	PILLAR: ParaspInaL muscLe segmentAtion pRoject - a comprehensive online resource to guide manual segmentation of paraspinal muscles from magnetic resonance imaging	Anstruther M; Rossini B; Zhang T; Liang T; Xiao Y; Fortin M;	37996857 SOH
9	Compatible-domain Transfer Learning for Breast Cancer Classification with Limited Annotated Data	Shamshiri MA; Krzyzak A; Kowal M; Korbicz J;	36758326 ENCS
10	Measures of motor segmentation from rapid isometric force pulses are reliable and differentiate Parkinson's disease from age-related slowing	Howard SL; Grenet D; Bellumori M; Knight CA;	35768733 PSYCHOLOGY
11	Spoken Word Segmentation in First and Second Language: When ERP and Behavioral Measures Diverge	Gilbert AC; Lee JG; Coulter K; Wolpert MA; Kousaie S; Gracco VL; Klein D; Titone D; Phillips NA; Baum SR;	34603133 PSYCHOLOGY
12	Sharp U-Net: Depthwise convolutional network for biomedical image segmentation	Zunair H; Ben Hamza A;	34348214 ENCS
13	LUMINOUS database: lumbar multifidus muscle segmentation from ultrasound images	Belasso CJ; Behboodi B; Benali H; Boily M; Rivaz H; Fortin M;	33097024 PERFORM
14	Two-stage ultrasound image segmentation using U-Net and test time augmentation.	Amiri M; Brooks R; Behboodi B; Rivaz H;	32350786 IMAGING
15	Statistical learning of multiple speech streams: A challenge for monolingual infants.	Benitez VL, Bulgarelli F, Byers-Heinlein K, Saffran JR, Weiss DJ	31444822 CONCORDIA
16	High resolution atlas of the venous brain vasculature from 7 T quantitative susceptibility maps.	Huck J, Wanner Y, Fan AP, Jäger AT, Grahl S, Schneider U, Villringer A, Steele CJ, Tardif CL, Bazin PL, Gauthier CJ	31278570 PSYCHOLOGY
17	The first MICCAI challenge on PET tumor segmentation.	Hatt M, Laurent B, Ouahabi A, Fayad H, Tan S, Li L, Lu W, Jaouen V, Tauber C, Czakon J, Drapejkowski F, Dyrka W, Camarasu-Pop S, Cervenansky F, Girard P, Glatard T, Kain M, Yao Y, Barillot C, Kirov A, Visvikis D	29268169 IMAGING
18	A dataset of multi-contrast population-averaged brain MRI atlases of a Parkinson׳s disease cohort.	Xiao Y, Fonov V, Chakravarty MM, Beriault S, Al Subaie F, Sadikot A, Pike GB, Bertrand G, Collins DL	28491942 PERFORM

Title:	High resolution atlas of the venous brain vasculature from 7 T quantitative susceptibility maps.
Authors:	Huck J, Wanner Y, Fan AP, Jäger AT, Grahl S, Schneider U, Villringer A, Steele CJ, Tardif CL, Bazin PL, Gauthier CJ
Link:	https://www.ncbi.nlm.nih.gov/pubmed/31278570?dopt=Abstract
DOI:	10.1007/s00429-019-01919-4
Publication:	Brain structure & function
Keywords:	Cerebral vasculature; QSM, UHF-MRI; Vein atlas; Vein segmentation; Venous vasculature;
PMID:	31278570	Category:	Brain Struct Funct	Date Added:	2019-08-07
Dept Affiliation:	PSYCHOLOGY 1 Department of Physics, Concordia University, 1455 Boulevard de Maisonneuve O, Montreal, QC, H3G 1M8, Canada. Julia.Huck@mail.concordia.ca. 2 Department of Physics, Concordia University, 1455 Boulevard de Maisonneuve O, Montreal, QC, H3G 1M8, Canada. 3 Universität Stuttgart, Stuttgart, Germany. 4 Stanford University, Stanford, USA. 5 Max-Planck-Institut fur Kognitions- und Neurowissenschaften, Leipzig, Germany. 6 Clinic for Cognitive Neurology, University of Leipzig, Leipzig, Germany. 7 Leipzig University Medical Centre, IFB Adiposity Diseases, Leipzig, Germany. 8 Leipzig University Medical Centre, Collaborative Research Centre, 1052-A5, Leipzig, Germany. 9 Department of Psychology, Concordia University, Montreal, Canada. 10 Department of Biomedical Engineering, McGill University, Montreal, Canada. 11 Montreal Neurological Institute, Montreal, Canada. 12 Faculty of Social and Behavioural Sciences, University of Amsterdam, Amsterdam, Netherlands. 13 Montreal Heart Institute, Montreal, Canada.

Description:

High resolution atlas of the venous brain vasculature from 7 T quantitative susceptibility maps.

Brain Struct Funct. 2019 Jul 05;:

Authors: Huck J, Wanner Y, Fan AP, Jäger AT, Grahl S, Schneider U, Villringer A, Steele CJ, Tardif CL, Bazin PL, Gauthier CJ

Abstract

The vascular organization of the human brain can determine neurological and neurophysiological functions, yet thus far it has not been comprehensively mapped. Aging and diseases such as dementia are known to be associated with changes to the vasculature and normative data could help detect these vascular changes in neuroimaging studies. Furthermore, given the well-known impact of venous vessels on the blood oxygen level dependent (BOLD) signal, information about the common location of veins could help detect biases in existing datasets. In this work, a quantitative atlas of the venous vasculature using quantitative susceptibility maps (QSM) acquired with a 0.6-mm isotropic resolution is presented. The Venous Neuroanatomy (VENAT) atlas was created from 5 repeated 7 Tesla MRI measurements in young and healthy volunteers (n?=?20, 10 females, mean age?=?25.1?±?2.5 years) using a two-step registration method on 3D segmentations of the venous vasculature. This cerebral vein atlas includes the average vessel location, diameter (mean: 0.84?±?0.33 mm) and curvature (0.11?±?0.05 mm-1) from all participants and provides an in vivo measure of the angio-architectonic organization of the human brain and its variability. This atlas can be used as a basis to understand changes in the vasculature during aging and neurodegeneration, as well as vascular and physiological effects in neuroimaging.

PMID: 31278570 [PubMed - as supplied by publisher]

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