MRIFreeDataset.zip | 193.09MB |
Type: Dataset
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Bibtex:
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Bibtex:
@article{, title= {MRI Lesion Segmentation in Multiple Sclerosis Database}, keywords= {}, author= {}, abstract= {MRI MS DB Description: In the IMT-Segmentation folder there are 38 folders representing data for each patient 38patients). In each patient folder we have: 1) MRI TIFF Images from first and second examination (0 months, 6-12 months) 2) Lesion segmentations (*.plq files). The delineation/s can be loaded into matlab i.e load(file.plq, '-.mat'); Then points can be drawn on the image. %How to load the point deliniations into MATLAB and plot them to the image. load('IM_00031_1.plq','-mat'); a=imread('IM_00031.tif'); figure, imshow(a), hold on, plot(yi,xi, 'LineWidth', 3), hold off; Further download information for the database may be obtained by contacting Prof. Christos P. Loizou (panloicy@logosnet.cy.net). ![](https://i.imgur.com/K2JypfI.png) ## Citation request 1. C.P. Loizou, V. Murray, M.S. Pattichis, I. Seimenis, M. Pantziaris, C.S. Pattichis, ìMulti-scale amplitude modulation-frequency modulation (AM-FM) texture analysis of multiple sclerosis in brain MRI images,î IEEE Trans. Inform. Tech. Biomed., vol. 15, no. 1, pp. 119-129, 2011. 2. C.P. Loizou, E.C. Kyriacou, I. Seimenis, M. Pantziaris, S. Petroudi, M. Karaolis, C.S. Pattichis, ìBrain white matter lesion classification in multiple sclerosis subjects for the prognosis of future disability,î Intelligent Decision Technologies Journal (IDT), vol. 7, pp. 3-10, 2013. 3. C.P. Loizou, M. Pantziaris, C.S. Pattichis, I. Seimenis, ìBrain MRI Image normalization in texture analysis of multiple sclerosisî, J. Biomed. Graph. & Comput., vol. 3, no.1, pp. 20-34, 2013. 4. C.P. Loizou, S. Petroudi, I. Seimenis, M. Pantziaris, C.S. Pattichis, Quantitative texture analysis of brain white matter lesions derived from T2-weighted MR images in MS patients with clinically isolated syndromeî, J. Neuroradiol., acepted. }, terms= {}, license= {}, superseded= {}, url= {http://www.medinfo.cs.ucy.ac.cy/doc/Publications/Datasets/} }
by omid306 at 2020-10-26 11:25:49 GMT
how can I find healthy and normal images of this dataset ?
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