No-reference perceptual CT image quality assessment based on a self-supervised learning framework

Accurate image quality assessment (IQA) is crucial to optimize computed tomography (CT) image protocols while keeping the radiation dose as low as reasonably achievable. In the medical domain, IQA is based on how well an image provides a useful and efficient presentation necessary for physicians to...

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Veröffentlicht in:	Machine learning: science and technology 2022-12, Vol.3 (4), p.45033
Hauptverfasser:	Lee, Wonkyeong, Cho, Eunbyeol, Kim, Wonjin, Choi, Hyebin, Beck, Kyongmin Sarah, Yoon, Hyun Jung, Baek, Jongduk, Choi, Jang-Hwan
Format:	Artikel
Sprache:	eng
Schlagworte:	Computed tomography Image quality Machine learning Medical imaging no-reference image quality assessment Object recognition perceptual image quality Quality assessment Radiation dosage radiation dose Self-supervised learning
Online-Zugang:	Volltext
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