707 related articles for article (PubMed ID: 24529948)
1. Clinical validation of an algorithm for rapid and accurate automated segmentation of intracoronary optical coherence tomography images.
Chatzizisis YS; Koutkias VG; Toutouzas K; Giannopoulos A; Chouvarda I; Riga M; Antoniadis AP; Cheimariotis G; Doulaverakis C; Tsampoulatidis I; Bouki K; Kompatsiaris I; Stefanadis C; Maglaveras N; Giannoglou GD
Int J Cardiol; 2014 Apr; 172(3):568-80. PubMed ID: 24529948
[TBL] [Abstract][Full Text] [Related]
2. Fully automatic three-dimensional quantitative analysis of intracoronary optical coherence tomography: method and Validation.
Sihan K; Botha C; Post F; de Winter S; Gonzalo N; Regar E; Serruys PJ; Hamers R; Bruining N
Catheter Cardiovasc Interv; 2009 Dec; 74(7):1058-65. PubMed ID: 19521990
[TBL] [Abstract][Full Text] [Related]
3. In-vivo segmentation and quantification of coronary lesions by optical coherence tomography images for a lesion type definition and stenosis grading.
Celi S; Berti S
Med Image Anal; 2014 Oct; 18(7):1157-68. PubMed ID: 25077844
[TBL] [Abstract][Full Text] [Related]
4. Fully Automated Lumen Segmentation Method for Intracoronary Optical Coherence Tomography.
Pociask E; Malinowski KP; Ślęzak M; Jaworek-Korjakowska J; Wojakowski W; Roleder T
J Healthc Eng; 2018; 2018():1414076. PubMed ID: 30792831
[TBL] [Abstract][Full Text] [Related]
5. Accuracy and reproducibility of automated drusen segmentation in eyes with non-neovascular age-related macular degeneration.
Nittala MG; Ruiz-Garcia H; Sadda SR
Invest Ophthalmol Vis Sci; 2012 Dec; 53(13):8319-24. PubMed ID: 23150629
[TBL] [Abstract][Full Text] [Related]
6. A novel approach for quantitative analysis of intracoronary optical coherence tomography: high inter-observer agreement with computer-assisted contour detection.
Tanimoto S; Rodriguez-Granillo G; Barlis P; de Winter S; Bruining N; Hamers R; Knappen M; Verheye S; Serruys PW; Regar E
Catheter Cardiovasc Interv; 2008 Aug; 72(2):228-35. PubMed ID: 18324698
[TBL] [Abstract][Full Text] [Related]
7. Accurate and reproducible reconstruction of coronary arteries and endothelial shear stress calculation using 3D OCT: comparative study to 3D IVUS and 3D QCA.
Toutouzas K; Chatzizisis YS; Riga M; Giannopoulos A; Antoniadis AP; Tu S; Fujino Y; Mitsouras D; Doulaverakis C; Tsampoulatidis I; Koutkias VG; Bouki K; Li Y; Chouvarda I; Cheimariotis G; Maglaveras N; Kompatsiaris I; Nakamura S; Reiber JH; Rybicki F; Karvounis H; Stefanadis C; Tousoulis D; Giannoglou GD
Atherosclerosis; 2015 Jun; 240(2):510-9. PubMed ID: 25932791
[TBL] [Abstract][Full Text] [Related]
8. Segmentation of the geographic atrophy in spectral-domain optical coherence tomography and fundus autofluorescence images.
Hu Z; Medioni GG; Hernandez M; Hariri A; Wu X; Sadda SR
Invest Ophthalmol Vis Sci; 2013 Dec; 54(13):8375-83. PubMed ID: 24265015
[TBL] [Abstract][Full Text] [Related]
9. Reconstruction of stented coronary arteries from optical coherence tomography images: Feasibility, validation, and repeatability of a segmentation method.
Chiastra C; Montin E; Bologna M; Migliori S; Aurigemma C; Burzotta F; Celi S; Dubini G; Migliavacca F; Mainardi L
PLoS One; 2017; 12(6):e0177495. PubMed ID: 28574987
[TBL] [Abstract][Full Text] [Related]
10. Dual modality intravascular optical coherence tomography (OCT) and near-infrared fluorescence (NIRF) imaging: a fully automated algorithm for the distance-calibration of NIRF signal intensity for quantitative molecular imaging.
Ughi GJ; Verjans J; Fard AM; Wang H; Osborn E; Hara T; Mauskapf A; Jaffer FA; Tearney GJ
Int J Cardiovasc Imaging; 2015 Feb; 31(2):259-68. PubMed ID: 25341407
[TBL] [Abstract][Full Text] [Related]
11. Agreement of corneal epithelial profiles produced by automated segmentation of SD-OCT images having different optical resolutions.
Shen M; Xu Z; Yang C; Leng L; Liu J; Chen Q; Wang J; Lu F
Eye Contact Lens; 2014 Mar; 40(2):99-105. PubMed ID: 24492238
[TBL] [Abstract][Full Text] [Related]
12. Linear-regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography.
Yong YL; Tan LK; McLaughlin RA; Chee KH; Liew YM
J Biomed Opt; 2017 Dec; 22(12):1-9. PubMed ID: 29274144
[TBL] [Abstract][Full Text] [Related]
13. Automatic segmentation of optical coherence tomography pullbacks of coronary arteries treated with bioresorbable vascular scaffolds: Application to hemodynamics modeling.
Bologna M; Migliori S; Montin E; Rampat R; Dubini G; Migliavacca F; Mainardi L; Chiastra C
PLoS One; 2019; 14(3):e0213603. PubMed ID: 30870477
[TBL] [Abstract][Full Text] [Related]
14. Methodology for fully automated segmentation and plaque characterization in intracoronary optical coherence tomography images.
Athanasiou LS; Bourantas CV; Rigas G; Sakellarios AI; Exarchos TP; Siogkas PK; Ricciardi A; Naka KK; Papafaklis MI; Michalis LK; Prati F; Fotiadis DI
J Biomed Opt; 2014 Feb; 19(2):026009. PubMed ID: 24525828
[TBL] [Abstract][Full Text] [Related]
15. Reproducibility of coronary Fourier domain optical coherence tomography: quantitative analysis of in vivo stented coronary arteries using three different software packages.
Okamura T; Gonzalo N; Gutiérrez-Chico JL; Serruys PW; Bruining N; de Winter S; Dijkstra J; Commossaris KH; van Geuns RJ; van Soest G; Ligthart J; Regar E
EuroIntervention; 2010 Aug; 6(3):371-9. PubMed ID: 20884417
[TBL] [Abstract][Full Text] [Related]
16. FloatingCanvas: quantification of 3D retinal structures from spectral-domain optical coherence tomography.
Zhu H; Crabb DP; Schlottmann PG; Ho T; Garway-Heath DF
Opt Express; 2010 Nov; 18(24):24595-610. PubMed ID: 21164806
[TBL] [Abstract][Full Text] [Related]
17. A framework for computational fluid dynamic analyses of patient-specific stented coronary arteries from optical coherence tomography images.
Migliori S; Chiastra C; Bologna M; Montin E; Dubini G; Aurigemma C; Fedele R; Burzotta F; Mainardi L; Migliavacca F
Med Eng Phys; 2017 Sep; 47():105-116. PubMed ID: 28711588
[TBL] [Abstract][Full Text] [Related]
18. Automatic vessel lumen segmentation and stent strut detection in intravascular optical coherence tomography.
Tsantis S; Kagadis GC; Katsanos K; Karnabatidis D; Bourantas G; Nikiforidis GC
Med Phys; 2012 Jan; 39(1):503-13. PubMed ID: 22225321
[TBL] [Abstract][Full Text] [Related]
19. In vivo assessment of retinal neuronal layers in multiple sclerosis with manual and automated optical coherence tomography segmentation techniques.
Seigo MA; Sotirchos ES; Newsome S; Babiarz A; Eckstein C; Ford E; Oakley JD; Syc SB; Frohman TC; Ratchford JN; Balcer LJ; Frohman EM; Calabresi PA; Saidha S
J Neurol; 2012 Oct; 259(10):2119-30. PubMed ID: 22418995
[TBL] [Abstract][Full Text] [Related]
20. A novel active contour model for fully automated segmentation of intravascular ultrasound images: in vivo validation in human coronary arteries.
Giannoglou GD; Chatzizisis YS; Koutkias V; Kompatsiaris I; Papadogiorgaki M; Mezaris V; Parissi E; Diamantopoulos P; Strintzis MG; Maglaveras N; Parcharidis GE; Louridas GE
Comput Biol Med; 2007 Sep; 37(9):1292-302. PubMed ID: 17291482
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
