Shireen Y. Elhabian
Shireen Y. Elhabian
Associate Professor, Kahlert School of Computing, SCI Institute, University of Utah
Потвърден имейл адрес: sci.utah.edu - Начална страница
Moving object detection in spatial domain using background removal techniques-state-of-art
SY Elhabian, KM El-Sayed, SH Ahmed
Recent patents on computer science 1 (1), 32-54, 2008
Shapeworks: particle-based shape correspondence and visualization software
J Cates, S Elhabian, R Whitaker
Statistical shape and deformation analysis, 257-298, 2017
Content-centric networks: an overview, applications and research challenges
SH Ahmed, SH Bouk, D Kim
Springer, 2016
DeepSSM: a deep learning framework for statistical shape modeling from raw images
R Bhalodia, SY Elhabian, L Kavan, RT Whitaker
Shape in Medical Imaging: International Workshop, ShapeMI 2018, Held in …, 2018
Toward precise pulmonary nodule descriptors for nodule type classification
A Farag, S Elhabian, J Graham, A Farag, R Falk
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2010: 13th …, 2010
Which two-dimensional radiographic measurements of cam femoroacetabular impingement best describe the three-dimensional shape of the proximal femur?
PR Atkins, YJ Shin, P Agrawal, SY Elhabian, RT Whitaker, JA Weiss, ...
Clinical Orthopaedics and Related Research® 477 (1), 242-253, 2019
Quantitative comparison of cortical bone thickness using correspondence‐based shape modeling in patients with cam femoroacetabular impingement
PR Atkins, SY Elhabian, P Agrawal, MD Harris, RT Whitaker, JA Weiss, ...
Journal of Orthopaedic Research 35 (8), 1743-1753, 2017
Benchmarking off-the-shelf statistical shape modeling tools in clinical applications
A Goparaju, K Iyer, A Bône, N Hu, HB Henninger, AE Anderson, ...
Medical image analysis 76, 102271, 2022
Statistical shape and deformation analysis
J Cates, S Elhabian, R Whitaker, G Zheng, S Li, G Székely
Elsevier, 2017
Uncertain-deepssm: From images to probabilistic shape models
J Adams, R Bhalodia, S Elhabian
Shape in Medical Imaging: International Workshop, ShapeMI 2020, Held in …, 2020
A tutorial on data reduction linear discriminant analysis (LDA)
AA Farag, SY Elhabian
University of Louisville, Tech. Rep, 2008
Small-molecule mimicry hunting strategy in the imperial cone snail, Conus imperialis
JP Torres, Z Lin, M Watkins, PF Salcedo, RP Baskin, S Elhabian, ...
Science advances 7 (11), eabf2704, 2021
On the evaluation and validation of off-the-shelf statistical shape modeling tools: a clinical application
A Goparaju, I Csecs, A Morris, E Kholmovski, N Marrouche, R Whitaker, ...
Shape in Medical Imaging: International Workshop, ShapeMI 2018, Held in …, 2018
Quantification of nodule detection in chest CT: A clinical investigation based on the ELCAP study
AA Farag, SY Elhabian, SA Elshazly, AA Farag
Proc. of Second International Workshop on Pulmonary Image Processing in …, 2009
Deep learning for end-to-end atrial fibrillation recurrence estimation
R Bhalodia, A Goparaju, T Sodergren, A Morris, E Kholmovski, ...
2018 Computing in Cardiology Conference (CinC) 45, 1-4, 2018
DeepSSM: A blueprint for image-to-shape deep learning models
R Bhalodia, S Elhabian, J Adams, W Tao, L Kavan, R Whitaker
Medical Image Analysis 91, 103034, 2024
Coracoacromial morphology: a contributor to recurrent traumatic anterior glenohumeral instability?
M Jacxsens, SY Elhabian, SE Brady, PN Chalmers, RZ Tashjian, ...
Journal of shoulder and elbow surgery 28 (7), 1316-1325. e1, 2019
A cooperative autoencoder for population-based regularization of CNN image registration
R Bhalodia, SY Elhabian, L Kavan, RT Whitaker
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
Skeletal shape correspondence through entropy
L Tu, M Styner, J Vicory, S Elhabian, R Wang, J Hong, B Paniagua, ...
IEEE transactions on medical imaging 37 (1), 1-11, 2017
From images to probabilistic anatomical shapes: A deep variational bottleneck approach
J Adams, S Elhabian
International Conference on Medical Image Computing and Computer-Assisted …, 2022
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