174 related articles for article (PubMed ID: 26621795)
1. Differentiating brain metastases from different pathological types of lung cancers using texture analysis of T1 postcontrast MR.
Li Z; Mao Y; Li H; Yu G; Wan H; Li B
Magn Reson Med; 2016 Nov; 76(5):1410-1419. PubMed ID: 26621795
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. 2D and 3D texture analysis to differentiate brain metastases on MR images: proceed with caution.
Béresová M; Larroza A; Arana E; Varga J; Balkay L; Moratal D
MAGMA; 2018 Apr; 31(2):285-294. PubMed ID: 28939952
[TBL] [Abstract][Full Text] [Related]
5. Use of texture analysis based on contrast-enhanced MRI to predict treatment response to chemoradiotherapy in nasopharyngeal carcinoma.
Liu J; Mao Y; Li Z; Zhang D; Zhang Z; Hao S; Li B
J Magn Reson Imaging; 2016 Aug; 44(2):445-55. PubMed ID: 26778191
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.
Ortiz-Ramón R; Larroza A; Ruiz-España S; Arana E; Moratal D
Eur Radiol; 2018 Nov; 28(11):4514-4523. PubMed ID: 29761357
[TBL] [Abstract][Full Text] [Related]
8. Brain metastases detection on MR by means of three-dimensional tumor-appearance template matching.
Pérez-Ramírez Ú; Arana E; Moratal D
J Magn Reson Imaging; 2016 Sep; 44(3):642-52. PubMed ID: 26934581
[TBL] [Abstract][Full Text] [Related]
9. Characterization of breast cancer types by texture analysis of magnetic resonance images.
Holli K; Lääperi AL; Harrison L; Luukkaala T; Toivonen T; Ryymin P; Dastidar P; Soimakallio S; Eskola H
Acad Radiol; 2010 Feb; 17(2):135-41. PubMed ID: 19945302
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Texture-based classification of different gastric tumors at contrast-enhanced CT.
Ba-Ssalamah A; Muin D; Schernthaner R; Kulinna-Cosentini C; Bastati N; Stift J; Gore R; Mayerhoefer ME
Eur J Radiol; 2013 Oct; 82(10):e537-43. PubMed ID: 23910996
[TBL] [Abstract][Full Text] [Related]
12. An artificial neural network (ANN)-based lung-tumor motion predictor for intrafractional MR tumor tracking.
Yun J; Mackenzie M; Rathee S; Robinson D; Fallone BG
Med Phys; 2012 Jul; 39(7):4423-33. PubMed ID: 22830775
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Application of Texture Analysis in Diagnosis of Multiple Sclerosis by Magnetic Resonance Imaging.
Abbasian Ardakani A; Gharbali A; Saniei Y; Mosarrezaii A; Nazarbaghi S
Glob J Health Sci; 2015 Mar; 7(6):68-78. PubMed ID: 26153164
[TBL] [Abstract][Full Text] [Related]
15. A novel content-based active contour model for brain tumor segmentation.
Sachdeva J; Kumar V; Gupta I; Khandelwal N; Ahuja CK
Magn Reson Imaging; 2012 Jun; 30(5):694-715. PubMed ID: 22459443
[TBL] [Abstract][Full Text] [Related]
16. Differentiation between glioblastoma, brain metastasis and subtypes using radiomics analysis.
Artzi M; Bressler I; Ben Bashat D
J Magn Reson Imaging; 2019 Aug; 50(2):519-528. PubMed ID: 30635952
[TBL] [Abstract][Full Text] [Related]
17. Dynamic MRI of solitary pulmonary nodules: comparison of enhancement patterns of malignant and benign small peripheral lung lesions.
Kono R; Fujimoto K; Terasaki H; Müller NL; Kato S; Sadohara J; Hayabuchi N; Takamori S
AJR Am J Roentgenol; 2007 Jan; 188(1):26-36. PubMed ID: 17179342
[TBL] [Abstract][Full Text] [Related]
18. Multiparametric magnetic resonance imaging to differentiate high-grade gliomas and brain metastases.
Mouthuy N; Cosnard G; Abarca-Quinones J; Michoux N
J Neuroradiol; 2012 Dec; 39(5):301-7. PubMed ID: 22197404
[TBL] [Abstract][Full Text] [Related]
19. Breast cancer molecular subtype classifier that incorporates MRI features.
Sutton EJ; Dashevsky BZ; Oh JH; Veeraraghavan H; Apte AP; Thakur SB; Morris EA; Deasy JO
J Magn Reson Imaging; 2016 Jul; 44(1):122-9. PubMed ID: 26756416
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]