78 related articles for article (PubMed ID: 23771304)
1. A likelihood and local constraint level set model for liver tumor segmentation from CT volumes.
Li C; Wang X; Eberl S; Fulham M; Yin Y; Chen J; Feng DD
IEEE Trans Biomed Eng; 2013 Oct; 60(10):2967-77. PubMed ID: 23771304
[TBL] [Abstract][Full Text] [Related]
2. A conditional statistical shape model with integrated error estimation of the conditions; application to liver segmentation in non-contrast CT images.
Tomoshige S; Oost E; Shimizu A; Watanabe H; Nawano S
Med Image Anal; 2014 Jan; 18(1):130-43. PubMed ID: 24184436
[TBL] [Abstract][Full Text] [Related]
3. Semi-automatic liver tumor segmentation with hidden Markov measure field model and non-parametric distribution estimation.
Häme Y; Pollari M
Med Image Anal; 2012 Jan; 16(1):140-9. PubMed ID: 21742543
[TBL] [Abstract][Full Text] [Related]
4. Semi-automatic level set segmentation of liver tumors combining a spiral-scanning technique with supervised fuzzy pixel classification.
Smeets D; Loeckx D; Stijnen B; De Dobbelaer B; Vandermeulen D; Suetens P
Med Image Anal; 2010 Feb; 14(1):13-20. PubMed ID: 19828356
[TBL] [Abstract][Full Text] [Related]
5. Supervised variational model with statistical inference and its application in medical image segmentation.
Li C; Wang X; Eberl S; Fulham M; Yin Y; Dagan Feng D
IEEE Trans Biomed Eng; 2015 Jan; 62(1):196-207. PubMed ID: 25099393
[TBL] [Abstract][Full Text] [Related]
6. Mammography segmentation with maximum likelihood active contours.
Rahmati P; Adler A; Hamarneh G
Med Image Anal; 2012 Aug; 16(6):1167-86. PubMed ID: 22831774
[TBL] [Abstract][Full Text] [Related]
7. A generic probabilistic active shape model for organ segmentation.
Wimmer A; Soza G; Hornegger J
Med Image Comput Comput Assist Interv; 2009; 12(Pt 2):26-33. PubMed ID: 20426092
[TBL] [Abstract][Full Text] [Related]
8. A density distance augmented Chan-Vese active contour for CT bone segmentation.
Truc PT; Lee S; Kim TS
Annu Int Conf IEEE Eng Med Biol Soc; 2008; 2008():482-5. PubMed ID: 19162698
[TBL] [Abstract][Full Text] [Related]
9. Tumor sensitive matching flow: A variational method to detecting and segmenting perihepatic and perisplenic ovarian cancer metastases on contrast-enhanced abdominal CT.
Liu J; Wang S; Linguraru MG; Yao J; Summers RM
Med Image Anal; 2014 Jul; 18(5):725-39. PubMed ID: 24835180
[TBL] [Abstract][Full Text] [Related]
10. Rapid assessment of liver volumetry by a novel automated segmentation algorithm.
Zahel T; Wildgruber M; Ardon R; Schuster T; Rummeny EJ; Dobritz M
J Comput Assist Tomogr; 2013; 37(4):577-82. PubMed ID: 23863535
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Intracranial aneurysm segmentation in 3D CT angiography: method and quantitative validation with and without prior noise filtering.
Firouzian A; Manniesing R; Flach ZH; Risselada R; van Kooten F; Sturkenboom MC; van der Lugt A; Niessen WJ
Eur J Radiol; 2011 Aug; 79(2):299-304. PubMed ID: 20346606
[TBL] [Abstract][Full Text] [Related]
13. Atlas-based automated segmentation of spleen and liver using adaptive enhancement estimation.
Linguraru MG; Sandberg JK; Li Z; Pura JA; Summers RM
Med Image Comput Comput Assist Interv; 2009; 12(Pt 2):1001-8. PubMed ID: 20426209
[TBL] [Abstract][Full Text] [Related]
14. Automated segmentation of the liver from 3D CT images using probabilistic atlas and multilevel statistical shape model.
Okada T; Shimada R; Hori M; Nakamoto M; Chen YW; Nakamura H; Sato Y
Acad Radiol; 2008 Nov; 15(11):1390-403. PubMed ID: 18995190
[TBL] [Abstract][Full Text] [Related]
15. A homotopy-based sparse representation for fast and accurate shape prior modeling in liver surgical planning.
Wang G; Zhang S; Xie H; Metaxas DN; Gu L
Med Image Anal; 2015 Jan; 19(1):176-86. PubMed ID: 25461336
[TBL] [Abstract][Full Text] [Related]
16. Level set method with automatic selective local statistics for brain tumor segmentation in MR images.
Thapaliya K; Pyun JY; Park CS; Kwon GR
Comput Med Imaging Graph; 2013; 37(7-8):522-37. PubMed ID: 24148784
[TBL] [Abstract][Full Text] [Related]
17. Simulation of biphasic CT findings in hepatic cellular carcinoma by a two-level physiological model.
Kretowski M; Bezy-Wendling J; Coupe P
IEEE Trans Biomed Eng; 2007 Mar; 54(3):538-42. PubMed ID: 17355068
[TBL] [Abstract][Full Text] [Related]
18. Automatic model-guided segmentation of the human brain ventricular system from CT images.
Liu J; Huang S; Ihar V; Ambrosius W; Lee LC; Nowinski WL
Acad Radiol; 2010 Jun; 17(6):718-26. PubMed ID: 20457415
[TBL] [Abstract][Full Text] [Related]
19. Three-dimensional morphometric analysis for hepatectomy of centrally located hepatocellular carcinoma: a pilot study.
Tian F; Wu JX; Rong WQ; Wang LM; Wu F; Yu WB; An SL; Liu FQ; Feng L; Bi C; Liu YH
World J Gastroenterol; 2015 Apr; 21(15):4607-19. PubMed ID: 25914470
[TBL] [Abstract][Full Text] [Related]
20. Segmentation of neck lymph nodes in CT datasets with stable 3D mass-spring models segmentation of neck lymph nodes.
Dornheim J; Seim H; Preim B; Hertel I; Strauss G
Acad Radiol; 2007 Nov; 14(11):1389-99. PubMed ID: 17964462
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]