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Compressed sensing and deep learning reconstruction for women’s pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice

Takahiro Ueda, Yoshiharu Ohno, Kaori Yamamoto, Akiyoshi Iwase, Takashi Fukuba, Satomu Hanamatsu, Yuki Obama, Hirotaka Ikeda, Masato Ikedo, Masao Yui, Kazuhiro Murayama, Hiroshi Toyama

2020European Journal of Radiology89 citationsDOIOpen Access PDF

Topics & Concepts

MedicineClinical PracticeRadiologyArtificial intelligenceImage qualityMedical physicsCompressed sensingDeep learningQuality (philosophy)Noise reductionImage (mathematics)Computer visionPhysical therapyComputer sciencePhilosophyEpistemologyAdvanced X-ray Imaging TechniquesMRI in cancer diagnosisDigital Radiography and Breast Imaging
Compressed sensing and deep learning reconstruction for women’s pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice | Litcius