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A review: artificial intelligence in image-guided spinal surgery.
Zeng, Jiahang; Fu, Qiang.
Afiliação
  • Zeng J; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.
  • Fu Q; Department of Orthopedics, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Expert Rev Med Devices ; 21(8): 689-700, 2024 Aug.
Article em En | MEDLINE | ID: mdl-39115295
ABSTRACT

INTRODUCTION:

Due to the complex anatomy of the spine and the intricate surgical procedures involved, spinal surgery demands a high level of technical expertise from surgeons. The clinical application of image-guided spinal surgery has significantly enhanced lesion visualization, reduced operation time, and improved surgical outcomes. AREAS COVERED This article reviews the latest advancements in deep learning and artificial intelligence in image-guided spinal surgery, aiming to provide references and guidance for surgeons, engineers, and researchers involved in this field. EXPERT OPINION Our analysis indicates that image-guided spinal surgery, augmented by artificial intelligence, outperforms traditional spinal surgery techniques. Moving forward, it is imperative to collect a more expansive dataset to further ensure the procedural safety of such surgeries. These insights carry significant implications for the integration of artificial intelligence in the medical field, ultimately poised to enhance the proficiency of surgeons and improve surgical outcomes.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Coluna Vertebral / Inteligência Artificial / Cirurgia Assistida por Computador Limite: Humans Idioma: En Revista: Expert Rev Med Devices Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Coluna Vertebral / Inteligência Artificial / Cirurgia Assistida por Computador Limite: Humans Idioma: En Revista: Expert Rev Med Devices Ano de publicação: 2024 Tipo de documento: Article