185 related articles for article (PubMed ID: 29807107)
1. A fast level set method for inhomogeneous image segmentation with adaptive scale parameter.
Huang G; Ji H; Zhang W
Magn Reson Imaging; 2018 Oct; 52():33-45. PubMed ID: 29807107
[TBL] [Abstract][Full Text] [Related]
2. A level set method based on domain transformation and bias correction for MRI brain tumor segmentation.
Khosravanian A; Rahmanimanesh M; Keshavarzi P; Mozaffari S
J Neurosci Methods; 2021 Mar; 352():109091. PubMed ID: 33515604
[TBL] [Abstract][Full Text] [Related]
3. Segmentation of MR image using local and global region based geodesic model.
Li X; Jiang D; Shi Y; Li W
Biomed Eng Online; 2015 Feb; 14():8. PubMed ID: 25971306
[TBL] [Abstract][Full Text] [Related]
4. Active contours driven by local and global fitted image models for image segmentation robust to intensity inhomogeneity.
Akram F; Garcia MA; Puig D
PLoS One; 2017; 12(4):e0174813. PubMed ID: 28376124
[TBL] [Abstract][Full Text] [Related]
5. Split Bregman method based level set formulations for segmentation and correction with application to MR images and color images.
Yang Y; Tian D; Jia W; Shu X; Wu B
Magn Reson Imaging; 2019 Apr; 57():50-67. PubMed ID: 30326258
[TBL] [Abstract][Full Text] [Related]
6. A level set method for multiple sclerosis lesion segmentation.
Zhao Y; Guo S; Luo M; Shi X; Bilello M; Zhang S; Li C
Magn Reson Imaging; 2018 Jun; 49():94-100. PubMed ID: 28522366
[TBL] [Abstract][Full Text] [Related]
7. Image-guided regularization level set evolution for MR image segmentation and bias field correction.
Wang L; Pan C
Magn Reson Imaging; 2014 Jan; 32(1):71-83. PubMed ID: 24239334
[TBL] [Abstract][Full Text] [Related]
8. A fast and reliable noise-resistant medical image segmentation and bias field correction model.
Yang Y; Tian D; Wu B
Magn Reson Imaging; 2018 Dec; 54():15-31. PubMed ID: 30075185
[TBL] [Abstract][Full Text] [Related]
9. An active contour model for the segmentation of images with intensity inhomogeneities and bias field estimation.
Huang C; Zeng L
PLoS One; 2015; 10(3):e0120399. PubMed ID: 25837416
[TBL] [Abstract][Full Text] [Related]
10. A Level Set Approach to Image Segmentation With Intensity Inhomogeneity.
Zhang K; Zhang L; Lam KM; Zhang D
IEEE Trans Cybern; 2016 Feb; 46(2):546-57. PubMed ID: 25781973
[TBL] [Abstract][Full Text] [Related]
11. Active Contours Using Additive Local and Global Intensity Fitting Models for Intensity Inhomogeneous Image Segmentation.
Soomro S; Akram F; Kim JH; Soomro TA; Choi KN
Comput Math Methods Med; 2016; 2016():9675249. PubMed ID: 27800011
[TBL] [Abstract][Full Text] [Related]
12. Hybrid two-stage active contour method with region and edge information for intensity inhomogeneous image segmentation.
Soomro S; Munir A; Choi KN
PLoS One; 2018; 13(1):e0191827. PubMed ID: 29377911
[TBL] [Abstract][Full Text] [Related]
13. Robust generative asymmetric GMM for brain MR image segmentation.
Ji Z; Xia Y; Zheng Y
Comput Methods Programs Biomed; 2017 Nov; 151():123-138. PubMed ID: 28946994
[TBL] [Abstract][Full Text] [Related]
14. Automatic segmentation for brain MR images via a convex optimized segmentation and bias field correction coupled model.
Chen Y; Zhao B; Zhang J; Zheng Y
Magn Reson Imaging; 2014 Sep; 32(7):941-55. PubMed ID: 24832358
[TBL] [Abstract][Full Text] [Related]
15. A level set method for image segmentation in the presence of intensity inhomogeneities with application to MRI.
Li C; Huang R; Ding Z; Gatenby JC; Metaxas DN; Gore JC
IEEE Trans Image Process; 2011 Jul; 20(7):2007-16. PubMed ID: 21518662
[TBL] [Abstract][Full Text] [Related]
16. A Global Inhomogeneous Intensity Clustering- (GINC-) Based Active Contour Model for Image Segmentation and Bias Correction.
Feng C; Yang J; Lou C; Li W; Yu K; Zhao D
Comput Math Methods Med; 2020; 2020():7595174. PubMed ID: 32565883
[TBL] [Abstract][Full Text] [Related]
17. Multi-level adaptive segmentation of multi-parameter MR brain images.
Zavaljevski A; Dhawan AP; Gaskil M; Ball W; Johnson JD
Comput Med Imaging Graph; 2000; 24(2):87-98. PubMed ID: 10767588
[TBL] [Abstract][Full Text] [Related]
18. A multi-objective optimization approach for brain MRI segmentation using fuzzy entropy clustering and region-based active contour methods.
Pham TX; Siarry P; Oulhadj H
Magn Reson Imaging; 2019 Sep; 61():41-65. PubMed ID: 31108153
[TBL] [Abstract][Full Text] [Related]
19. Segmentation of intensity inhomogeneous brain MR images using active contours.
Akram F; Kim JH; Lim HU; Choi KN
Comput Math Methods Med; 2014; 2014():194614. PubMed ID: 25143780
[TBL] [Abstract][Full Text] [Related]
20. Fast and robust brain tumor segmentation using level set method with multiple image information.
Lok KH; Shi L; Zhu X; Wang D
J Xray Sci Technol; 2017; 25(2):301-312. PubMed ID: 28269819
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]