Keyword search (4,163 papers available)

"Segmentation" Keyword-tagged Publications:

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:Measures of motor segmentation from rapid isometric force pulses are reliable and differentiate Parkinson's disease from age-related slowing
Authors:Howard SLGrenet DBellumori MKnight CA
Link:pubmed.ncbi.nlm.nih.gov/35768733/
DOI:10.1007/s00221-022-06398-4
Publication:Experimental brain research
Keywords:BradykinesiaMotor segmentationMuscleNeurodegenerative diseaseParkinson's diseaseRate of force development
PMID:35768733 Category: Date Added:2022-06-30
Dept Affiliation: PSYCHOLOGY
1 Dept. of Kinesiology and Health Education, The University of Texas at Austin, Austin, TX, USA.
2 Department of Psychology, Concordia University, Montreal, QC, Canada.
3 Kinesiology Department, California State University, Monterey Bay, Seaside, CA, USA.
4 Department of Kinesiology and Applied Physiology, University of Delaware, 344 The Tower at STAR, 100 Discovery Blvd., Newark, DE, 19716, USA. caknight@udel.edu.

Description:

Some people with Parkinson's disease (PD) have disruptions in motor output during rapid isometric muscle contractions. Measures of such disruptions (motor segmentation) may help clarify disease subtype, progression, or effects of therapeutic interventions. We investigated the potential utility of segmentation measures by testing two hypotheses that are fundamental to measurement and evaluation. First, measures of motor segmentation are reliable from day to day (intraclass correlation coefficient > 0.8). Second, that measures of motor segmentation have the sensitivity to differentiate between people with PD and older adults. 10 subjects with PD had a mean age of 70.1 years, Hoehn-Yahr stage < 3, and median levodopa equivalent daily dose of 350 mg. Older adult (mean age 81.9 years) reference data are from a previously published study. Each subject provided approximately 87 rapid isometric index finger abduction force pulses up to 65% of their maximal isometric force for calculation of force pulse measures. Measures were computed for the excitation, transition, and relaxation phases of each force pulse. Measures of motor segmentation had high reliability and presented large (Cohen's D > 0.8) and significant (p < 0.05) group differences. In bivariate plots of selected measures, motor segmentation marked a departure of PD from age-related slowing. Across all subjects, greater segmentation was associated with greater impairments in rate control and a longer time to reach peak force (all Spearman's ? > 0.8). These results support the potential utility of the motor segmentation measures by satisfying requirements for reliability and the sensitivity to indicate deviations from age-related slowing in motor output.




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