Feasibility of a Generative Adversarial Network for Artifact Removal in Experimental Photoacoustic Imaging.

Shahid, Husnain; Khalid, Adnan; Yue, Yaoting; Liu, Xin; Ta, Dean

Shahid, Husnain; Khalid, Adnan; Yue, Yaoting; Liu, Xin; Ta, Dean.

Afiliação

Shahid H; Center for Biomedical Engineering, Fudan University, China.
Khalid A; School of Information and Communication Engineering, Tianjin University, China.
Yue Y; Center for Biomedical Engineering, Fudan University, China.
Liu X; Academy for Engineering and Technology, Fudan University, Shanghai, China. Electronic address: xin_liu@fudan.edu.cn.
Ta D; Center for Biomedical Engineering, Fudan University, China; Academy for Engineering and Technology, Fudan University, Shanghai, China. Electronic address: tda@fudan.edu.cn.

Ultrasound Med Biol ; 48(8): 1628-1643, 2022 08.

Article em En | MEDLINE | ID: mdl-35660105

Assuntos

Artefatos; Técnicas Fotoacústicas; Estudos de Viabilidade; Processamento de Imagem Assistida por Computador/métodos; Razão Sinal-Ruído

Palavras-chave

Generative adversarial networks; Image denoising; Image reconstruction; Photoacoustic tomography; Subsampling

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Artefatos / Técnicas Fotoacústicas Tipo de estudo: Qualitative_research Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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