Robust learning-based x-ray image denoising-potential pitfalls, their analysis and solutions.

Hariharan, Sai Gokul; Kaethner, Christian; Strobel, Norbert; Kowarschik, Markus; Fahrig, Rebecca; Navab, Nassir

Hariharan, Sai Gokul; Kaethner, Christian; Strobel, Norbert; Kowarschik, Markus; Fahrig, Rebecca; Navab, Nassir.

Afiliação

Hariharan SG; Computer Aided Medical Procedures, Technische Universität München, Munich, Germany.
Kaethner C; Siemens Healthineers AG, Advanced Therapies, Forchheim, Germany.
Strobel N; Siemens Healthineers AG, Advanced Therapies, Forchheim, Germany.
Kowarschik M; Institute of Medical Engineering Schweinfurt, University of Applied Sciences, Würzburg-Schweinfurt, Schweinfurt, Germany.
Fahrig R; Computer Aided Medical Procedures, Technische Universität München, Munich, Germany.
Navab N; Siemens Healthineers AG, Advanced Therapies, Forchheim, Germany.

Biomed Phys Eng Express ; 8(3)2022 04 07.

Article em En | MEDLINE | ID: mdl-34714256

Assuntos

Artefatos; Tomografia Computadorizada por Raios X; Humanos; Imagens de Fantasmas; Razão Sinal-Ruído; Tomografia Computadorizada por Raios X/métodos; Raios X

Palavras-chave

deep learning; denoising; low-dose x-ray imaging; noise simulation

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tomografia Computadorizada por Raios X / Artefatos Idioma: En Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Alemanha

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