BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

174 related articles for article (PubMed ID: 29265012)

  • 1. 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]  

  • 2. 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]  

  • 3. 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]  

  • 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. 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]  

  • 6. Automatic 3D CT liver segmentation based on fast global minimization of probabilistic active contour.
    Jin R; Wang M; Xu L; Lu J; Song E; Ma G
    Med Phys; 2023 Apr; 50(4):2100-2120. PubMed ID: 36413182
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. 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]  

  • 9. 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]  

  • 10. 3D surface voxel tracing corrector for accurate bone segmentation.
    Guo H; Song S; Wang J; Guo M; Cheng Y; Wang Y; Tamura S
    Int J Comput Assist Radiol Surg; 2018 Oct; 13(10):1549-1563. PubMed ID: 29916062
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A two-stage rule-constrained seedless region growing approach for mandibular body segmentation in MRI.
    Ji DX; Foong KW; Ong SH
    Int J Comput Assist Radiol Surg; 2013 Sep; 8(5):723-32. PubMed ID: 23397281
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Liver segmentation from abdominal CT volumes based on level set and sparse shape composition.
    Li Y; Zhao YQ; Zhang F; Liao M; Yu LL; Chen BF; Wang YJ
    Comput Methods Programs Biomed; 2020 Oct; 195():105533. PubMed ID: 32502932
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Toward accurate tooth segmentation from computed tomography images using a hybrid level set model.
    Gan Y; Xia Z; Xiong J; Zhao Q; Hu Y; Zhang J
    Med Phys; 2015 Jan; 42(1):14-27. PubMed ID: 25563244
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automatic liver segmentation from abdominal CT volumes using graph cuts and border marching.
    Liao M; Zhao YQ; Liu XY; Zeng YZ; Zou BJ; Wang XF; Shih FY
    Comput Methods Programs Biomed; 2017 May; 143():1-12. PubMed ID: 28391807
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A Unified Level Set Framework Combining Hybrid Algorithms for Liver and Liver Tumor Segmentation in CT Images.
    Zheng Z; Zhang X; Xu H; Liang W; Zheng S; Shi Y
    Biomed Res Int; 2018; 2018():3815346. PubMed ID: 30159326
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Automatic liver segmentation in computed tomography using general-purpose shape modeling methods.
    Spinczyk D; Krasoń A
    Biomed Eng Online; 2018 May; 17(1):65. PubMed ID: 29843736
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Automatic multi-organ segmentation from abdominal CT volumes with LLE-based graph partitioning and 3D Chan-Vese model.
    Tang P; Zhao YQ; Liao M
    Comput Biol Med; 2021 Dec; 139():105030. PubMed ID: 34800809
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. 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]  

    [Next]    [New Search]
    of 9.