کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6775682 1432011 2018 32 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Medical image super-resolution by using multi-dictionary and random forest
ترجمه فارسی عنوان
تصویر پزشکی فوق العاده با استفاده از چند فرهنگ لغت و جنگل تصادفی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
چکیده انگلیسی
Smart City has become the direction of the development of city. Telemedicine is an important part of Smart City. Telemedicine always provides clinical health care according to the medical images of the patient. High resolution images are expected for remote diagnosis. Super-resolution technology can improve the resolution of medical images. Recently, sparse coding based super-resolution has attracted more attentions. Sparse coding based super-resolution tries to find the sparse representation of low-resolution (LR) image patches from low resolution dictionary, then reconstructs high-resolution (HR) image patches using sparse representation and HR dictionary. In this paper, we propose a sparse-based scheme for medical image super-resolution. First, we jointly divide the training patches into several clusters. Multiple dictionaries are learned from each cluster to collectively provide the least super-resolution error for the training patches. Second, random forest is trained based on the training patches and their cluster labels. Finally, for an input LR image patches, we use trained random forest to determine which cluster the patch belong to, then use the corresponding dictionary to reconstruct the patch. Thus, all the input LR patches are reconstructed with smallest error. All the reconstructed HR patches are synthesized into a completed HR image. The proposed scheme is applied to test a set of medical images. Experimental results show that both objective evaluation (PSNR) and subjective evaluation (visual effect) are improved when compare to other example-based methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Sustainable Cities and Society - Volume 37, February 2018, Pages 358-370
نویسندگان
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