267 related articles for article (PubMed ID: 19826872)
1. Automatic lung segmentation in CT images with accurate handling of the hilar region.
De Nunzio G; Tommasi E; Agrusti A; Cataldo R; De Mitri I; Favetta M; Maglio S; Massafra A; Quarta M; Torsello M; Zecca I; Bellotti R; Tangaro S; Calvini P; Camarlinghi N; Falaschi F; Cerello P; Oliva P
J Digit Imaging; 2011 Feb; 24(1):11-27. PubMed ID: 19826872
[TBL] [Abstract][Full Text] [Related]
2. Automatic detection of lung nodules in CT datasets based on stable 3D mass-spring models.
Cascio D; Magro R; Fauci F; Iacomi M; Raso G
Comput Biol Med; 2012 Nov; 42(11):1098-109. PubMed ID: 23020972
[TBL] [Abstract][Full Text] [Related]
3. A Segmentation Framework of Pulmonary Nodules in Lung CT Images.
Mukhopadhyay S
J Digit Imaging; 2016 Feb; 29(1):86-103. PubMed ID: 26055544
[TBL] [Abstract][Full Text] [Related]
4. Combining 2D wavelet edge highlighting and 3D thresholding for lung segmentation in thin-slice CT.
Korfiatis P; Skiadopoulos S; Sakellaropoulos P; Kalogeropoulou C; Costaridou L
Br J Radiol; 2007 Dec; 80(960):996-1004. PubMed ID: 18065645
[TBL] [Abstract][Full Text] [Related]
5. Segmentation of lung lesions on CT scans using watershed, active contours, and Markov random field.
Tan Y; Schwartz LH; Zhao B
Med Phys; 2013 Apr; 40(4):043502. PubMed ID: 23556926
[TBL] [Abstract][Full Text] [Related]
6. A new computationally efficient CAD system for pulmonary nodule detection in CT imagery.
Messay T; Hardie RC; Rogers SK
Med Image Anal; 2010 Jun; 14(3):390-406. PubMed ID: 20346728
[TBL] [Abstract][Full Text] [Related]
7. Automated segmentation refinement of small lung nodules in CT scans by local shape analysis.
Diciotti S; Lombardo S; Falchini M; Picozzi G; Mascalchi M
IEEE Trans Biomed Eng; 2011 Dec; 58(12):3418-28. PubMed ID: 21914567
[TBL] [Abstract][Full Text] [Related]
8. Automated segmentation of lungs with severe interstitial lung disease in CT.
Wang J; Li F; Li Q
Med Phys; 2009 Oct; 36(10):4592-9. PubMed ID: 19928090
[TBL] [Abstract][Full Text] [Related]
9. Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans.
Lassen BC; Jacobs C; Kuhnigk JM; van Ginneken B; van Rikxoort EM
Phys Med Biol; 2015 Feb; 60(3):1307-23. PubMed ID: 25591989
[TBL] [Abstract][Full Text] [Related]
10. Three-dimensional lung tumor segmentation from x-ray computed tomography using sparse field active models.
Awad J; Owrangi A; Villemaire L; O'Riordan E; Parraga G; Fenster A
Med Phys; 2012 Feb; 39(2):851-65. PubMed ID: 22320795
[TBL] [Abstract][Full Text] [Related]
11. Computer-aided diagnosis of pulmonary nodules on CT scans: segmentation and classification using 3D active contours.
Way TW; Hadjiiski LM; Sahiner B; Chan HP; Cascade PN; Kazerooni EA; Bogot N; Zhou C
Med Phys; 2006 Jul; 33(7):2323-37. PubMed ID: 16898434
[TBL] [Abstract][Full Text] [Related]
12. Three-dimensional lung nodule segmentation and shape variance analysis to detect lung cancer with reduced false positives.
Krishnamurthy S; Narasimhan G; Rengasamy U
Proc Inst Mech Eng H; 2016 Jan; 230(1):58-70. PubMed ID: 26721427
[TBL] [Abstract][Full Text] [Related]
13. Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans.
Rikhari H; Baidya Kayal E; Ganguly S; Sasi A; Sharma S; Dheeksha DS; Saini M; Rangarajan K; Bakhshi S; Kandasamy D; Mehndiratta A
Int J Comput Assist Radiol Surg; 2024 Feb; 19(2):261-272. PubMed ID: 37594684
[TBL] [Abstract][Full Text] [Related]
14. Smoothing lung segmentation surfaces in three-dimensional X-ray CT images using anatomic guidance.
Ukil S; Reinhardt JM
Acad Radiol; 2005 Dec; 12(12):1502-11. PubMed ID: 16321738
[TBL] [Abstract][Full Text] [Related]
15. An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT.
Alilou M; Beig N; Orooji M; Rajiah P; Velcheti V; Rakshit S; Reddy N; Yang M; Jacono F; Gilkeson RC; Linden P; Madabhushi A
Med Phys; 2017 Jul; 44(7):3556-3569. PubMed ID: 28295386
[TBL] [Abstract][Full Text] [Related]
16. Segmentation of pulmonary nodules in three-dimensional CT images by use of a spiral-scanning technique.
Wang J; Engelmann R; Li Q
Med Phys; 2007 Dec; 34(12):4678-89. PubMed ID: 18196795
[TBL] [Abstract][Full Text] [Related]
17. Deep Deconvolutional Residual Network Based Automatic Lung Nodule Segmentation.
Singadkar G; Mahajan A; Thakur M; Talbar S
J Digit Imaging; 2020 Jun; 33(3):678-684. PubMed ID: 32026218
[TBL] [Abstract][Full Text] [Related]
18. Many Is Better Than One: An Integration of Multiple Simple Strategies for Accurate Lung Segmentation in CT Images.
Shi Z; Ma J; Zhao M; Liu Y; Feng Y; Zhang M; He L; Suzuki K
Biomed Res Int; 2016; 2016():1480423. PubMed ID: 27635395
[TBL] [Abstract][Full Text] [Related]
19. Automatic lung segmentation for accurate quantitation of volumetric X-ray CT images.
Hu S; Hoffman EA; Reinhardt JM
IEEE Trans Med Imaging; 2001 Jun; 20(6):490-8. PubMed ID: 11437109
[TBL] [Abstract][Full Text] [Related]
20. Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset.
Xu M; Qi S; Yue Y; Teng Y; Xu L; Yao Y; Qian W
Biomed Eng Online; 2019 Jan; 18(1):2. PubMed ID: 30602393
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
