167 related articles for article (PubMed ID: 31071158)
1. Novel stochastic framework for automatic segmentation of human thigh MRI volumes and its applications in spinal cord injured individuals.
Mesbah S; Shalaby AM; Stills S; Soliman AM; Willhite A; Harkema SJ; Rejc E; El-Baz AS
PLoS One; 2019; 14(5):e0216487. PubMed ID: 31071158
[TBL] [Abstract][Full Text] [Related]
2. Convolutional Neural Network-Based Automated Segmentation of the Spinal Cord and Contusion Injury: Deep Learning Biomarker Correlates of Motor Impairment in Acute Spinal Cord Injury.
McCoy DB; Dupont SM; Gros C; Cohen-Adad J; Huie RJ; Ferguson A; Duong-Fernandez X; Thomas LH; Singh V; Narvid J; Pascual L; Kyritsis N; Beattie MS; Bresnahan JC; Dhall S; Whetstone W; Talbott JF;
AJNR Am J Neuroradiol; 2019 Apr; 40(4):737-744. PubMed ID: 30923086
[TBL] [Abstract][Full Text] [Related]
3. Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans.
da Silva GLF; Diniz PS; Ferreira JL; França JVF; Silva AC; de Paiva AC; de Cavalcanti EAA
Med Biol Eng Comput; 2020 Sep; 58(9):1947-1964. PubMed ID: 32566988
[TBL] [Abstract][Full Text] [Related]
4. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.
Tong N; Gou S; Yang S; Ruan D; Sheng K
Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285
[TBL] [Abstract][Full Text] [Related]
5. Fully-integrated framework for the segmentation and registration of the spinal cord white and gray matter.
Dupont SM; De Leener B; Taso M; Le Troter A; Nadeau S; Stikov N; Callot V; Cohen-Adad J
Neuroimage; 2017 Apr; 150():358-372. PubMed ID: 27663988
[TBL] [Abstract][Full Text] [Related]
6. A fast stochastic framework for automatic MR brain images segmentation.
Ismail M; Soliman A; Ghazal M; Switala AE; Gimel'farb G; Barnes GN; Khalil A; El-Baz A
PLoS One; 2017; 12(11):e0187391. PubMed ID: 29136034
[TBL] [Abstract][Full Text] [Related]
7. In-depth learning of automatic segmentation of shoulder joint magnetic resonance images based on convolutional neural networks.
Mu X; Cui Y; Bian R; Long L; Zhang D; Wang H; Shen Y; Wu J; Zou G
Comput Methods Programs Biomed; 2021 Nov; 211():106325. PubMed ID: 34536635
[TBL] [Abstract][Full Text] [Related]
8. Volume measurements of individual muscles in human quadriceps femoris using atlas-based segmentation approaches.
Le Troter A; Fouré A; Guye M; Confort-Gouny S; Mattei JP; Gondin J; Salort-Campana E; Bendahan D
MAGMA; 2016 Apr; 29(2):245-57. PubMed ID: 26983429
[TBL] [Abstract][Full Text] [Related]
9. Analysis of diffusion tensor measurements of the human cervical spinal cord based on semiautomatic segmentation of the white and gray matter.
Dostál M; Keřkovský M; Korit Áková E; Němcová E; Stulík J; Staňková M; Bernard V
J Magn Reson Imaging; 2018 Nov; 48(5):1217-1227. PubMed ID: 29707834
[TBL] [Abstract][Full Text] [Related]
10. Spinal Cord Segmentation by One Dimensional Normalized Template Matching: A Novel, Quantitative Technique to Analyze Advanced Magnetic Resonance Imaging Data.
Cadotte A; Cadotte DW; Livne M; Cohen-Adad J; Fleet D; Mikulis D; Fehlings MG
PLoS One; 2015; 10(10):e0139323. PubMed ID: 26445367
[TBL] [Abstract][Full Text] [Related]
11. Deep learning for automatic segmentation of thigh and leg muscles.
Agosti A; Shaqiri E; Paoletti M; Solazzo F; Bergsland N; Colelli G; Savini G; Muzic SI; Santini F; Deligianni X; Diamanti L; Monforte M; Tasca G; Ricci E; Bastianello S; Pichiecchio A
MAGMA; 2022 Jun; 35(3):467-483. PubMed ID: 34665370
[TBL] [Abstract][Full Text] [Related]
12. Deep learning-based automatic pipeline for quantitative assessment of thigh muscle morphology and fatty infiltration.
Gaj S; Eck BL; Xie D; Lartey R; Lo C; Zaylor W; Yang M; Nakamura K; Winalski CS; Spindler KP; Li X
Magn Reson Med; 2023 Jun; 89(6):2441-2455. PubMed ID: 36744695
[TBL] [Abstract][Full Text] [Related]
13. Automated assessment of thigh composition using machine learning for Dixon magnetic resonance images.
Yang YX; Chong MS; Tay L; Yew S; Yeo A; Tan CH
MAGMA; 2016 Oct; 29(5):723-31. PubMed ID: 27026244
[TBL] [Abstract][Full Text] [Related]
14. Deep convolutional neural network for segmentation of thoracic organs-at-risk using cropped 3D images.
Feng X; Qing K; Tustison NJ; Meyer CH; Chen Q
Med Phys; 2019 May; 46(5):2169-2180. PubMed ID: 30830685
[TBL] [Abstract][Full Text] [Related]
15. Validation of an active shape model-based semi-automated segmentation algorithm for the analysis of thigh muscle and adipose tissue cross-sectional areas.
Kemnitz J; Eckstein F; Culvenor AG; Ruhdorfer A; Dannhauer T; Ring-Dimitriou S; Sänger AM; Wirth W
MAGMA; 2017 Oct; 30(5):489-503. PubMed ID: 28455629
[TBL] [Abstract][Full Text] [Related]
16. Fully automatic 3D segmentation of the thoracolumbar spinal cord and the vertebral canal from T2-weighted MRI using K-means clustering algorithm.
Sabaghian S; Dehghani H; Batouli SAH; Khatibi A; Oghabian MA
Spinal Cord; 2020 Jul; 58(7):811-820. PubMed ID: 32132652
[TBL] [Abstract][Full Text] [Related]
17. Automatic muscle and fat segmentation in the thigh from T1-Weighted MRI.
Orgiu S; Lafortuna CL; Rastelli F; Cadioli M; Falini A; Rizzo G
J Magn Reson Imaging; 2016 Mar; 43(3):601-10. PubMed ID: 26268693
[TBL] [Abstract][Full Text] [Related]
18. The Generalized Log-Ratio Transformation: Learning Shape and Adjacency Priors for Simultaneous Thigh Muscle Segmentation.
Andrews S; Hamarneh G
IEEE Trans Med Imaging; 2015 Sep; 34(9):1773-87. PubMed ID: 25700442
[TBL] [Abstract][Full Text] [Related]
19. Clinical evaluation of fully automated thigh muscle and adipose tissue segmentation using a U-Net deep learning architecture in context of osteoarthritic knee pain.
Kemnitz J; Baumgartner CF; Eckstein F; Chaudhari A; Ruhdorfer A; Wirth W; Eder SK; Konukoglu E
MAGMA; 2020 Aug; 33(4):483-493. PubMed ID: 31872357
[TBL] [Abstract][Full Text] [Related]
20. An investigation of the effect of fat suppression and dimensionality on the accuracy of breast MRI segmentation using U-nets.
Fashandi H; Kuling G; Lu Y; Wu H; Martel AL
Med Phys; 2019 Mar; 46(3):1230-1244. PubMed ID: 30609062
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
