234 related articles for article (PubMed ID: 26501155)
1. 3D automatic liver segmentation using feature-constrained Mahalanobis distance in CT images.
Salman Al-Shaikhli SD; Yang MY; Rosenhahn B
Biomed Tech (Berl); 2016 Aug; 61(4):401-12. PubMed ID: 26501155
[TBL] [Abstract][Full Text] [Related]
2. Automatic 3D liver location and segmentation via convolutional neural network and graph cut.
Lu F; Wu F; Hu P; Peng Z; Kong D
Int J Comput Assist Radiol Surg; 2017 Feb; 12(2):171-182. PubMed ID: 27604760
[TBL] [Abstract][Full Text] [Related]
3. Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model.
He B; Huang C; Sharp G; Zhou S; Hu Q; Fang C; Fan Y; Jia F
Med Phys; 2016 May; 43(5):2421. PubMed ID: 27147353
[TBL] [Abstract][Full Text] [Related]
4. Blood vessel-based liver segmentation using the portal phase of an abdominal CT dataset.
Maklad AS; Matsuhiro M; Suzuki H; Kawata Y; Niki N; Satake M; Moriyama N; Utsunomiya T; Shimada M
Med Phys; 2013 Nov; 40(11):113501. PubMed ID: 24320472
[TBL] [Abstract][Full Text] [Related]
5. Shape-intensity prior level set combining probabilistic atlas and probability map constrains for automatic liver segmentation from abdominal CT images.
Wang J; Cheng Y; Guo C; Wang Y; Tamura S
Int J Comput Assist Radiol Surg; 2016 May; 11(5):817-26. PubMed ID: 26646416
[TBL] [Abstract][Full Text] [Related]
6. Automatic 3D liver segmentation based on deep learning and globally optimized surface evolution.
Hu P; Wu F; Peng J; Liang P; Kong D
Phys Med Biol; 2016 Dec; 61(24):8676-8698. PubMed ID: 27880735
[TBL] [Abstract][Full Text] [Related]
7. A 3D global-to-local deformable mesh model based registration and anatomy-constrained segmentation method for image guided prostate radiotherapy.
Zhou J; Kim S; Jabbour S; Goyal S; Haffty B; Chen T; Levinson L; Metaxas D; Yue NJ
Med Phys; 2010 Mar; 37(3):1298-308. PubMed ID: 20384267
[TBL] [Abstract][Full Text] [Related]
8. [Three-dimensional CT liver image segmentation based on hierarchical contextual active contour].
Ji H; He J; Yang X
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2014 Apr; 31(2):405-12. PubMed ID: 25039151
[TBL] [Abstract][Full Text] [Related]
9. A variational approach to liver segmentation using statistics from multiple sources.
Zheng S; Fang B; Li L; Gao M; Wang Y
Phys Med Biol; 2018 Jan; 63(2):025024. PubMed ID: 29265012
[TBL] [Abstract][Full Text] [Related]
10. Efficient liver segmentation in CT images based on graph cuts and bottleneck detection.
Liao M; Zhao YQ; Wang W; Zeng YZ; Yang Q; Shih FY; Zou BJ
Phys Med; 2016 Nov; 32(11):1383-1396. PubMed ID: 27771278
[TBL] [Abstract][Full Text] [Related]
11. Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.
Hu P; Wu F; Peng J; Bao Y; Chen F; Kong D
Int J Comput Assist Radiol Surg; 2017 Mar; 12(3):399-411. PubMed ID: 27885540
[TBL] [Abstract][Full Text] [Related]
12. 3D liver segmentation using multiple region appearances and graph cuts.
Peng J; Hu P; Lu F; Peng Z; Kong D; Zhang H
Med Phys; 2015 Dec; 42(12):6840-52. PubMed ID: 26632041
[TBL] [Abstract][Full Text] [Related]
13. 3D-SIFT-Flow for atlas-based CT liver image segmentation.
Xu Y; Xu C; Kuang X; Wang H; Chang EI; Huang W; Fan Y
Med Phys; 2016 May; 43(5):2229. PubMed ID: 27147335
[TBL] [Abstract][Full Text] [Related]
14. Automatic Liver Segmentation Based on Shape Constraints and Deformable Graph Cut in CT Images.
Li G; Chen X; Shi F; Zhu W; Tian J; Xiang D
IEEE Trans Image Process; 2015 Dec; 24(12):5315-29. PubMed ID: 26415173
[TBL] [Abstract][Full Text] [Related]
15. An Improved Fuzzy Connectedness Method for Automatic Three-Dimensional Liver Vessel Segmentation in CT Images.
Zhang R; Zhou Z; Wu W; Lin CC; Tsui PH; Wu S
J Healthc Eng; 2018; 2018():2376317. PubMed ID: 30510670
[TBL] [Abstract][Full Text] [Related]
16. 3D Liver Tumor Segmentation in CT Images Using Improved Fuzzy
Wu W; Wu S; Zhou Z; Zhang R; Zhang Y
Biomed Res Int; 2017; 2017():5207685. PubMed ID: 29090220
[TBL] [Abstract][Full Text] [Related]
17. Fully automatic liver segmentation in CT images using modified graph cuts and feature detection.
Huang Q; Ding H; Wang X; Wang G
Comput Biol Med; 2018 Apr; 95():198-208. PubMed ID: 29524804
[TBL] [Abstract][Full Text] [Related]
18. A generalized active shape model for segmentation of liver in low-contrast CT volumes.
Esfandiarkhani M; Foruzan AH
Comput Biol Med; 2017 Mar; 82():59-70. PubMed ID: 28161593
[TBL] [Abstract][Full Text] [Related]
19. Swarm Intelligence Integrated Graph-Cut for Liver Segmentation from 3D-CT Volumes.
Eapen M; Korah R; Geetha G
ScientificWorldJournal; 2015; 2015():823541. PubMed ID: 26689833
[TBL] [Abstract][Full Text] [Related]
20. Automatic liver segmentation from CT scans based on a statistical shape model.
Zhang X; Tian J; Deng K; Wu Y; Li X
Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():5351-4. PubMed ID: 21096258
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
