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Items: 1 to 20 of 59

1.

Comparison of 3-segmentation techniques for intraventricular and intracerebral hemorrhages in unenhanced computed tomography scans.

KN BP, Hu J, Morgan TC, Hanley D, Nowinski WL.

J Comput Assist Tomogr. 2012 Jan-Feb;36(1):109-20. doi: 10.1097/RCT.0b013e318245c1fa.

PMID:
22261780
2.

Segmentation and quantification of intra-ventricular/cerebral hemorrhage in CT scans by modified distance regularized level set evolution technique.

Prakash KN, Zhou S, Morgan TC, Hanley DF, Nowinski WL.

Int J Comput Assist Radiol Surg. 2012 Sep;7(5):785-98.

3.

A Brain Parenchyma Model-Based Segmentation of Intraventricular and Intracerebral Haemorrhage in CT Scans.

Bhanu Prakash KN, Morgan TC, Hanley DM, Nowinski WL.

Neuroradiol J. 2012 Jul;25(3):273-82. Epub 2012 Jun 26.

PMID:
24028979
4.

Detection and quantification of intracerebral and intraventricular hemorrhage from computed tomography images with adaptive thresholding and case-based reasoning.

Zhang Y, Chen M, Hu Q, Huang W.

Int J Comput Assist Radiol Surg. 2013 Nov;8(6):917-27. doi: 10.1007/s11548-013-0830-x. Epub 2013 Aug 23.

PMID:
23974978
5.

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. doi: 10.1016/j.acra.2010.02.013. Erratum in: Acad Radiol. 2010 Oct;17(10):1226.

PMID:
20457415
6.

Efficient denoising technique for CT images to enhance brain hemorrhage segmentation.

Bhadauria HS, Dewal ML.

J Digit Imaging. 2012 Dec;25(6):782-91. doi: 10.1007/s10278-012-9453-y.

7.

Characterization of intraventricular and intracerebral hematomas in non-contrast CT.

Nowinski WL, Gomolka RS, Qian G, Gupta V, Ullman NL, Hanley DF.

Neuroradiol J. 2014 Jun;27(3):299-315. doi: 10.15274/NRJ-2014-10042. Epub 2014 Jun 17.

8.

PItcHPERFeCT: Primary Intracranial Hemorrhage Probability Estimation using Random Forests on CT.

Muschelli J, Sweeney EM, Ullman NL, Vespa P, Hanley DF, Crainiceanu CM.

Neuroimage Clin. 2017 Feb 15;14:379-390. doi: 10.1016/j.nicl.2017.02.007. eCollection 2017.

9.

Automatic localization of solid organs on 3D CT images by a collaborative majority voting decision based on ensemble learning.

Zhou X, Wang S, Chen H, Hara T, Yokoyama R, Kanematsu M, Fujita H.

Comput Med Imaging Graph. 2012 Jun;36(4):304-13. doi: 10.1016/j.compmedimag.2011.12.004. Epub 2012 Mar 14.

PMID:
22421130
10.

Automatic segmentation of cerebrospinal fluid, white and gray matter in unenhanced computed tomography images.

Gupta V, Ambrosius W, Qian G, Blazejewska A, Kazmierski R, Urbanik A, Nowinski WL.

Acad Radiol. 2010 Nov;17(11):1350-8. doi: 10.1016/j.acra.2010.06.005. Epub 2010 Jul 15.

PMID:
20634108
11.

Extents of white matter lesions and increased intraventricular extension of intracerebral hemorrhage.

Kim BJ, Lee SH, Ryu WS, Kim CK, Chung JW, Kim D, Park HK, Yoon BW.

Crit Care Med. 2013 May;41(5):1325-31. doi: 10.1097/CCM.0b013e31827c05e9.

PMID:
23388516
12.

Post-processing sets of tilted CT volumes as a method for metal artifact reduction.

Ballhausen H, Reiner M, Ganswindt U, Belka C, Söhn M.

Radiat Oncol. 2014 May 15;9:114. doi: 10.1186/1748-717X-9-114.

13.

Automatic subarachnoid space segmentation and hemorrhage detection in clinical head CT scans.

Li YH, Zhang L, Hu QM, Li HW, Jia FC, Wu JH.

Int J Comput Assist Radiol Surg. 2012 Jul;7(4):507-16. doi: 10.1007/s11548-011-0664-3. Epub 2011 Nov 12.

PMID:
22081264
14.

[CT image segmentation based on automatic adaptive minimal fuzzy entropy measure].

Gong G, Feng C, Zhang H, Zhu Y.

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2008 Apr;25(2):304-8. Chinese.

PMID:
18610611
15.

Comparison of manual, semi- and fully automated heart segmentation for assessing global left ventricular function in multidetector computed tomography.

Plumhans C, Keil S, Ocklenburg C, Mühlenbruch G, Behrendt FF, Günther RW, Mahnken AH.

Invest Radiol. 2009 Aug;44(8):476-82. doi: 10.1097/RLI.0b013e3181aaf4e1.

PMID:
19561515
16.

4-D Imaging in cerebrovascular disorders by using 320-slice CT: feasibility and preliminary clinical experience.

Klingebiel R, Siebert E, Diekmann S, Wiener E, Masuhr F, Wagner M, Bauknecht HC, Dewey M, Bohner G.

Acad Radiol. 2009 Feb;16(2):123-9. doi: 10.1016/j.acra.2008.11.004.

PMID:
19124096
17.

Intrathoracic airway trees: segmentation and airway morphology analysis from low-dose CT scans.

Tschirren J, Hoffman EA, McLennan G, Sonka M.

IEEE Trans Med Imaging. 2005 Dec;24(12):1529-39.

18.

Intravascular functional maps of common neurovascular lesions derived from volumetric 4D CT data.

Barfett JJ, Fierstra J, Willems PW, Mikulis DJ, Krings T.

Invest Radiol. 2010 Jul;45(7):370-7. doi: 10.1097/RLI.0b013e3181e1939d.

PMID:
20479649
19.

Multidetector row CT angiography in spontaneous lobar intracerebral hemorrhage: a prospective comparison with conventional angiography.

Yoon DY, Chang SK, Choi CS, Kim WK, Lee JH.

AJNR Am J Neuroradiol. 2009 May;30(5):962-7. doi: 10.3174/ajnr.A1471. Epub 2009 Feb 4.

20.

Comparison of the effect of iterative reconstruction versus filtered back projection on cardiac CT postprocessing.

Spears JR, Schoepf UJ, Henzler T, Joshi G, Moscariello A, Vliegenthart R, Cho YJ, Apfaltrer P, Rowe G, Weininger M, Ebersberger U.

Acad Radiol. 2014 Mar;21(3):318-24. doi: 10.1016/j.acra.2013.11.008. Epub 2013 Dec 18.

PMID:
24360635

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