1457 related articles for article (PubMed ID: 26455963)
1. 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. PubMed ID: 26455963
[TBL] [Abstract][Full Text] [Related]
2. Computer-aided diagnosis of hepatic fibrosis: preliminary evaluation of MRI texture analysis using the finite difference method and an artificial neural network.
Kato H; Kanematsu M; Zhang X; Saio M; Kondo H; Goshima S; Fujita H
AJR Am J Roentgenol; 2007 Jul; 189(1):117-22. PubMed ID: 17579160
[TBL] [Abstract][Full Text] [Related]
3. 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 Jul; 44(7):3604-3614. PubMed ID: 28376281
[TBL] [Abstract][Full Text] [Related]
4. Automatic brain MR image denoising based on texture feature-based artificial neural networks.
Chang YN; Chang HH
Biomed Mater Eng; 2015; 26 Suppl 1():S1275-82. PubMed ID: 26405887
[TBL] [Abstract][Full Text] [Related]
5. Application of texture analysis on parametric T
Yu H; Touret AS; Li B; O'Brien M; Qureshi MM; Soto JA; Jara H; Anderson SW
J Magn Reson Imaging; 2017 Jan; 45(1):250-259. PubMed ID: 27249625
[TBL] [Abstract][Full Text] [Related]
6. Effects of magnetic resonance image interpolation on the results of texture-based pattern classification: a phantom study.
Mayerhoefer ME; Szomolanyi P; Jirak D; Berg A; Materka A; Dirisamer A; Trattnig S
Invest Radiol; 2009 Jul; 44(7):405-11. PubMed ID: 19465863
[TBL] [Abstract][Full Text] [Related]
7. A computer-aided diagnostic system to discriminate SPIO-enhanced magnetic resonance hepatocellular carcinoma by a neural network classifier.
Guo D; Qiu T; Bian J; Kang W; Zhang L
Comput Med Imaging Graph; 2009 Dec; 33(8):588-92. PubMed ID: 19656655
[TBL] [Abstract][Full Text] [Related]
8. Automated detection of prostatic adenocarcinoma from high-resolution ex vivo MRI.
Madabhushi A; Feldman MD; Metaxas DN; Tomaszeweski J; Chute D
IEEE Trans Med Imaging; 2005 Dec; 24(12):1611-25. PubMed ID: 16350920
[TBL] [Abstract][Full Text] [Related]
9. Texture analysis in non-contrast enhanced CT: impact of malignancy on texture in apparently disease-free areas of the liver.
Ganeshan B; Miles KA; Young RC; Chatwin CR
Eur J Radiol; 2009 Apr; 70(1):101-10. PubMed ID: 18242909
[TBL] [Abstract][Full Text] [Related]
10. Diagnostic Method of Liver Cirrhosis Based on MR Image Texture Feature Extraction and Classification Algorithm.
Chunmei X; Mei H; Yan Z; Haiying W
J Med Syst; 2019 Dec; 44(1):11. PubMed ID: 31802238
[TBL] [Abstract][Full Text] [Related]
11. Multilevel analysis of spatiotemporal association features for differentiation of tumor enhancement patterns in breast DCE-MRI.
Lee SH; Kim JH; Cho N; Park JS; Yang Z; Jung YS; Moon WK
Med Phys; 2010 Aug; 37(8):3940-56. PubMed ID: 20879557
[TBL] [Abstract][Full Text] [Related]
12. Cirrhosis classification based on texture classification of random features.
Liu H; Shao Y; Guo D; Zheng Y; Zhao Z; Qiu T
Comput Math Methods Med; 2014; 2014():536308. PubMed ID: 24707317
[TBL] [Abstract][Full Text] [Related]
13. Texture analysis for tissue discrimination on T1-weighted MR images of the knee joint in a multicenter study: Transferability of texture features and comparison of feature selection methods and classifiers.
Mayerhoefer ME; Breitenseher MJ; Kramer J; Aigner N; Hofmann S; Materka A
J Magn Reson Imaging; 2005 Nov; 22(5):674-80. PubMed ID: 16215966
[TBL] [Abstract][Full Text] [Related]
14. Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI.
Yu H; Buch K; Li B; O'Brien M; Soto J; Jara H; Anderson SW
J Magn Reson Imaging; 2015 Nov; 42(5):1259-65. PubMed ID: 26477447
[TBL] [Abstract][Full Text] [Related]
15. Quantitative texture analysis of brain white matter lesions derived from T2-weighted MR images in MS patients with clinically isolated syndrome.
Loizou CP; Petroudi S; Seimenis I; Pantziaris M; Pattichis CS
J Neuroradiol; 2015 Apr; 42(2):99-114. PubMed ID: 24970463
[TBL] [Abstract][Full Text] [Related]
16. Computer-aided diagnosis for preoperative invasion depth of gastric cancer with dual-energy spectral CT imaging.
Li C; Shi C; Zhang H; Hui C; Lam KM; Zhang S
Acad Radiol; 2015 Feb; 22(2):149-57. PubMed ID: 25249448
[TBL] [Abstract][Full Text] [Related]
17. Position tracking of moving liver lesion based on real-time registration between 2D ultrasound and 3D preoperative images.
Weon C; Hyun Nam W; Lee D; Lee JY; Ra JB
Med Phys; 2015 Jan; 42(1):335-47. PubMed ID: 25563273
[TBL] [Abstract][Full Text] [Related]
18. Hepatitis C related chronic liver cirrhosis: feasibility of texture analysis of MR images for classification of fibrosis stage and necroinflammatory activity grade.
Wu Z; Matsui O; Kitao A; Kozaka K; Koda W; Kobayashi S; Ryu Y; Minami T; Sanada J; Gabata T
PLoS One; 2015; 10(3):e0118297. PubMed ID: 25742285
[TBL] [Abstract][Full Text] [Related]
19. Texture-based classification of different single liver lesion based on SPAIR T2W MRI images.
Li Z; Mao Y; Huang W; Li H; Zhu J; Li W; Li B
BMC Med Imaging; 2017 Jul; 17(1):42. PubMed ID: 28705145
[TBL] [Abstract][Full Text] [Related]
20. Differential diagnosis of CT focal liver lesions using texture features, feature selection and ensemble driven classifiers.
Mougiakakou SG; Valavanis IK; Nikita A; Nikita KS
Artif Intell Med; 2007 Sep; 41(1):25-37. PubMed ID: 17624744
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]