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Deep Learning For Medical Image Super-Resolution For Precision Diagnosis

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dc.contributor.author Baraiya, Mehul M.
dc.contributor.author Kothari, Ashish M.
dc.date.accessioned 2023-05-03T07:09:44Z
dc.date.available 2023-05-03T07:09:44Z
dc.date.issued 2023-01
dc.identifier.citation Baraiya, M.M., & Kothari, A.M. (2023). Deep Learning For Medical Image Super-Resolution For Precision Diagnosis. Journal of Data Acquisition and Processing, 38(1), 1004-9037. https://sjcjycl.cn/DOI: 10.5281/zenodo.7747750 en_US
dc.identifier.issn 1004-9037
dc.identifier.uri http://10.9.150.37:8080/dspace//handle/atmiyauni/854
dc.description.abstract A study on deep learning for medical image super-resolution (MISR) and its prospective applications in medical imaging are presented in this research report. We investigate and evaluate the performance of two distinct methods to MISR employing CNNs and GANs on a dataset consisting of low-resolution medical pictures. Both of these techniques use artificial neural networks. Both CNN-based and GAN-based approaches were able to significantly improve the visual quality and diagnostic accuracy of medical images, with the GAN-based approach outperforming the CNN-based approach in terms of perceptual quality. Our experimental results show that both approaches can significantly improve the visual quality of medical images. We also examine the possible uses of deep learning for MISR in clinical diagnostics and medical technology, as well as assess the influence that various parameters have on the accuracy and visual quality of the models. This study makes a significant contribution to the expanding corpus of research on the use of deep learning to MISR and offers important new insights into the design, implementation, and improvement of deep learning models for use in medical imaging applications. en_US
dc.language.iso en en_US
dc.publisher Journal of Data Acquisition and Processing en_US
dc.subject Medical imaging en_US
dc.subject Clinical diagnosis en_US
dc.subject Image processing en_US
dc.subject Artificial intelligence en_US
dc.subject Image enhancement en_US
dc.title Deep Learning For Medical Image Super-Resolution For Precision Diagnosis en_US
dc.type Article en_US


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