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Items: 1 to 20 of 62

1.

Robust segmentation of intraretinal layers in the normal human fovea using a novel statistical model based on texture and shape analysis.

Kajić V, Povazay B, Hermann B, Hofer B, Marshall D, Rosin PL, Drexler W.

Opt Express. 2010 Jul 5;18(14):14730-44. doi: 10.1364/OE.18.014730.

PMID:
20639959
2.

Order preserving and shape prior constrained intra-retinal layer segmentation in optical coherence tomography.

Rathke F, Schmidt S, Schnörr C.

Med Image Comput Comput Assist Interv. 2011;14(Pt 3):370-7.

PMID:
22003721
3.

Automated choroidal segmentation of 1060 nm OCT in healthy and pathologic eyes using a statistical model.

Kajić V, Esmaeelpour M, Považay B, Marshall D, Rosin PL, Drexler W.

Biomed Opt Express. 2012 Jan 1;3(1):86-103. doi: 10.1364/BOE.3.000086. Epub 2011 Dec 12.

4.

Artifacts in automatic retinal segmentation using different optical coherence tomography instruments.

Giani A, Cigada M, Esmaili DD, Salvetti P, Luccarelli S, Marziani E, Luiselli C, Sabella P, Cereda M, Eandi C, Staurenghi G.

Retina. 2010 Apr;30(4):607-16. doi: 10.1097/IAE.0b013e3181c2e09d.

PMID:
20094011
5.

Intra-retinal layer segmentation in optical coherence tomography images.

Mishra A, Wong A, Bizheva K, Clausi DA.

Opt Express. 2009 Dec 21;17(26):23719-28. doi: 10.1364/OE.17.023719.

PMID:
20052083
6.

Automated segmentation of tissue structures in optical coherence tomography data.

Gasca F, Ramrath L, Huettmann G, Schweikard A.

J Biomed Opt. 2009 May-Jun;14(3):034046. doi: 10.1117/1.3156841.

PMID:
19566338
7.

Graph-based multi-surface segmentation of OCT data using trained hard and soft constraints.

Dufour PA, Ceklic L, Abdillahi H, Schröder S, De Dzanet S, Wolf-Schnurrbusch U, Kowal J.

IEEE Trans Med Imaging. 2013 Mar;32(3):531-43. doi: 10.1109/TMI.2012.2225152. Epub 2012 Oct 18.

PMID:
23086520
8.

Evaluation of potential image acquisition pitfalls during optical coherence tomography and their influence on retinal image segmentation.

Somfai GM, Salinas HM, Puliafito CA, Fernández DC.

J Biomed Opt. 2007 Jul-Aug;12(4):041209.

PMID:
17867798
9.
10.

Retinal thickness measurements from optical coherence tomography using a Markov boundary model.

Koozekanani D, Boyer K, Roberts C.

IEEE Trans Med Imaging. 2001 Sep;20(9):900-16.

PMID:
11585207
11.

Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography.

Ahlers C, Simader C, Geitzenauer W, Stock G, Stetson P, Dastmalchi S, Schmidt-Erfurth U.

Br J Ophthalmol. 2008 Feb;92(2):197-203. Epub 2007 Oct 26.

PMID:
17965102
12.

Adaptively learning local shape statistics for prostate segmentation in ultrasound.

Yan P, Xu S, Turkbey B, Kruecker J.

IEEE Trans Biomed Eng. 2011 Mar;58(3):633-41. doi: 10.1109/TBME.2010.2094195. Epub 2010 Nov 22.

PMID:
21097373
13.

Mutual information in coupled multi-shape model for medical image segmentation.

Tsai A, Wells W, Tempany C, Grimson E, Willsky A.

Med Image Anal. 2004 Dec;8(4):429-45.

PMID:
15567707
14.

Automated segmentation of retinal blood vessels in spectral domain optical coherence tomography scans.

Pilch M, Wenner Y, Strohmayr E, Preising M, Friedburg C, Meyer Zu Bexten E, Lorenz B, Stieger K.

Biomed Opt Express. 2012 Jul 1;3(7):1478-91. doi: 10.1364/BOE.3.001478. Epub 2012 Jun 4.

15.

Validation of bone segmentation and improved 3-D registration using contour coherency in CT data.

Wang LI, Greenspan M, Ellis R.

IEEE Trans Med Imaging. 2006 Mar;25(3):324-34.

PMID:
16524088
16.

Optical coherence tomography of the neurosensory retina in rhegmatogenous retinal detachment.

Hagimura N, Suto K, Iida T, Kishi S.

Am J Ophthalmol. 2000 Feb;129(2):186-90.

PMID:
10682971
17.

Comparison of 3 methods of automated internal carotid segmentation in human brain PET studies: application to the estimation of arterial input function.

Zanotti-Fregonara P, Maroy R, Comtat C, Jan S, Gaura V, Bar-Hen A, Ribeiro MJ, Trébossen R.

J Nucl Med. 2009 Mar;50(3):461-7. doi: 10.2967/jnumed.108.059642. Epub 2009 Feb 17.

18.

Foveal ganglion cell layer damage in ischemic diabetic maculopathy: correlation of optical coherence tomographic and anatomic changes.

Byeon SH, Chu YK, Lee H, Lee SY, Kwon OW.

Ophthalmology. 2009 Oct;116(10):1949-59.e8. doi: 10.1016/j.ophtha.2009.06.066. Epub 2009 Aug 21.

PMID:
19699533
19.

An analysis of early studies released by the Lung Imaging Database Consortium (LIDC).

Ross JC, Miller JV, Turner WD, Kelliher TP.

Acad Radiol. 2007 Nov;14(11):1382-8.

PMID:
17964461
20.

Intra-retinal layer segmentation in optical coherence tomography using an active contour approach.

Yazdanpanah A, Hamarneh G, Smith B, Sarunic M.

Med Image Comput Comput Assist Interv. 2009;12(Pt 2):649-56.

PMID:
20426167
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