Artificial Intelligence-Guided Segmentation and Path Planning Software for Transthoracic Lung Biopsy.

Journal: Journal of vascular and interventional radiology : JVIR
PMID: 38355040

Abstract

PURPOSE: To validate the sensitivity and specificity of a 3-dimensional (3D) convolutional neural network (CNN) artificial intelligence (AI) software for lung lesion detection and to establish concordance between AI-generated needle paths and those used in actual biopsy procedures.

Authors

  • Chow Wei Too
    Department of Vascular and Interventional Radiology, Singapore General Hospital, Singapore; Radiological Sciences Academic Clinical Program, SingHealth-Duke-NUS Academic Medical Centre, Singapore. Electronic address: too.chow.wei@singhealth.com.sg.
  • Khi Yung Fong
    Yong Loo Lin School of Medicine, National University of Singapore, Urology, Singapore, Singapore.
  • Guanqi Hang
    Department of Vascular and Interventional Radiology, Singapore General Hospital, Singapore, Singapore.
  • Takafumi Sato
    Department of Gastroenterological Surgery, Nagoya City University, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya, Aichi 467-8601, Japan.
  • Chiaw Qing Nyam
    NDR Medical Technology, Singapore, Singapore.
  • Siang Huei Leong
    NDR Medical Technology Pvt Ltd, Singapore.
  • Ka Wei Ng
    NDR Medical Technology, Pte. Ltd, Singapore.
  • Wei Lin Ng
    Department of Biomedical Imaging, Faculty of Medicine, University of Malaya, Kuala Lumpur, 50603, Malaysia.
  • Tatsuya Kawai
    Department of Radiology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.

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