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Items: 1 to 20 of 143

1.

Performance of topological texture features to classify fibrotic interstitial lung disease patterns.

Huber MB, Nagarajan MB, Leinsinger G, Eibel R, Ray LA, Wismüller A.

Med Phys. 2011 Apr;38(4):2035-44.

PMID:
21626936
2.

Robustness-Driven Feature Selection in Classification of Fibrotic Interstitial Lung Disease Patterns in Computed Tomography Using 3D Texture Features.

Chong DY, Kim HJ, Lo P, Young S, McNitt-Gray MF, Abtin F, Goldin JG, Brown MS.

IEEE Trans Med Imaging. 2016 Jan;35(1):144-57. doi: 10.1109/TMI.2015.2459064. Epub 2015 Jul 21.

PMID:
26208309
3.

Texture feature ranking with relevance learning to classify interstitial lung disease patterns.

Huber MB, Bunte K, Nagarajan MB, Biehl M, Ray LA, Wismüller A.

Artif Intell Med. 2012 Oct;56(2):91-7. doi: 10.1016/j.artmed.2012.07.001. Epub 2012 Sep 23.

4.
5.

Texture classification-based segmentation of lung affected by interstitial pneumonia in high-resolution CT.

Korfiatis P, Kalogeropoulou C, Karahaliou A, Kazantzi A, Skiadopoulos S, Costaridou L.

Med Phys. 2008 Dec;35(12):5290-302.

PMID:
19175088
6.

Computer-aided classification of interstitial lung diseases via MDCT: 3D adaptive multiple feature method (3D AMFM).

Xu Y, van Beek EJ, Hwanjo Y, Guo J, McLennan G, Hoffman EA.

Acad Radiol. 2006 Aug;13(8):969-78.

PMID:
16843849
7.

Enhanced Classification of Interstitial Lung Disease Patterns in HRCT Images Using Differential Lacunarity.

Vasconcelos V, Barroso J, Marques L, Silva JS.

Biomed Res Int. 2015;2015:672520. doi: 10.1155/2015/672520. Epub 2015 Dec 22.

8.

Feasibility of automated quantification of regional disease patterns depicted on high-resolution computed tomography in patients with various diffuse lung diseases.

Park SO, Seo JB, Kim N, Park SH, Lee YK, Park BW, Sung YS, Lee Y, Lee J, Kang SH.

Korean J Radiol. 2009 Sep-Oct;10(5):455-63. doi: 10.3348/kjr.2009.10.5.455. Epub 2009 Aug 25.

9.

Effective staging of fibrosis by the selected texture features of liver: Which one is better, CT or MR imaging?

Zhang X, Gao X, Liu BJ, Ma K, Yan W, Liling L, Yuhong H, Fujita H.

Comput Med Imaging Graph. 2015 Dec;46 Pt 2:227-36. doi: 10.1016/j.compmedimag.2015.09.003. Epub 2015 Sep 18.

PMID:
26455963
10.

Comparative performance analysis of state-of-the-art classification algorithms applied to lung tissue categorization.

Depeursinge A, Iavindrasana J, Hidki A, Cohen G, Geissbuhler A, Platon A, Poletti PA, Müller H.

J Digit Imaging. 2010 Feb;23(1):18-30. doi: 10.1007/s10278-008-9158-4. Epub 2008 Nov 4.

11.

Differentiation of Fat-Poor Angiomyolipoma from Clear Cell Renal Cell Carcinoma in Contrast-Enhanced MDCT Images using Quantitative Feature Classification.

Lee HS, Hong H, Jung DC, Park S, Kim J.

Med Phys. 2017 Apr 4. doi: 10.1002/mp.12258. [Epub ahead of print]

PMID:
28376281
12.

Computer-aided diagnosis in phase contrast imaging X-ray computed tomography for quantitative characterization of ex vivo human patellar cartilage.

Nagarajan MB, Coan P, Huber MB, Diemoz PC, Glaser C, Wismuller A.

IEEE Trans Biomed Eng. 2013 Oct;60(10):2896-903. doi: 10.1109/TBME.2013.2266325. Epub 2013 Jun 5.

13.

Quantitative assessment of change in regional disease patterns on serial HRCT of fibrotic interstitial pneumonia with texture-based automated quantification system.

Yoon RG, Seo JB, Kim N, Lee HJ, Lee SM, Lee YK, Song JW, Song JW, Kim DS.

Eur Radiol. 2013 Mar;23(3):692-701. doi: 10.1007/s00330-012-2634-8. Epub 2012 Aug 24.

PMID:
22918563
14.

Computer-assisted lip diagnosis on Traditional Chinese Medicine using multi-class support vector machines.

Li F, Zhao C, Xia Z, Wang Y, Zhou X, Li GZ.

BMC Complement Altern Med. 2012 Aug 16;12:127. doi: 10.1186/1472-6882-12-127.

15.

Automated classification of usual interstitial pneumonia using regional volumetric texture analysis in high-resolution computed tomography.

Depeursinge A, Chin AS, Leung AN, Terrone D, Bristow M, Rosen G, Rubin DL.

Invest Radiol. 2015 Apr;50(4):261-7. doi: 10.1097/RLI.0000000000000127.

16.

CT features of lung disease in patients with systemic sclerosis: comparison with idiopathic pulmonary fibrosis and nonspecific interstitial pneumonia.

Desai SR, Veeraraghavan S, Hansell DM, Nikolakopolou A, Goh NS, Nicholson AG, Colby TV, Denton CP, Black CM, du Bois RM, Wells AU.

Radiology. 2004 Aug;232(2):560-7.

PMID:
15286324
17.

Characterization of the interstitial lung diseases via density-based and texture-based analysis of computed tomography images of lung structure and function.

Hoffman EA, Reinhardt JM, Sonka M, Simon BA, Guo J, Saba O, Chon D, Samrah S, Shikata H, Tschirren J, Palagyi K, Beck KC, McLennan G.

Acad Radiol. 2003 Oct;10(10):1104-18.

PMID:
14587629
18.

Regional context-sensitive support vector machine classifier to improve automated identification of regional patterns of diffuse interstitial lung disease.

Lim J, Kim N, Seo JB, Lee YK, Lee Y, Kang SH.

J Digit Imaging. 2011 Dec;24(6):1133-40. doi: 10.1007/s10278-011-9367-0.

19.

Development and testing of texture discriminators for the analysis of trabecular bone in proximal femur radiographs.

Huber MB, Carballido-Gamio J, Fritscher K, Schubert R, Haenni M, Hengg C, Majumdar S, Link TM.

Med Phys. 2009 Nov;36(11):5089-98.

PMID:
19994519
20.

Classification of small lesions in dynamic breast MRI: Eliminating the need for precise lesion segmentation through spatio-temporal analysis of contrast enhancement over time.

Nagarajan MB, Huber MB, Schlossbauer T, Leinsinger G, Krol A, Wismüller A.

Mach Vis Appl. 2013 Oct 1;24(7). doi: 10.1007/s00138-012-0456-y.

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