Fully automatic deep learning-based lung parenchyma segmentation and boundary correction in thoracic CT scans.

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作者： Himanshu,Rikhari ^[1] ; Esha,Baidya Kayal ^[1] ; Shuvadeep,Ganguly ^[2] ; Archana,Sasi ^[2] ; Swetambri,Sharma ^[2] ; D S,Dheeksha ^[3] ; Manish,Saini ^[3] ; Krithika,Rangarajan ^[4] ; Sameer,Bakhshi ^[2] ; Devasenathipathy,Kandasamy ^[3] ; Amit,Mehndiratta ^[5]

作者单位： Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India. ^[1] All India Institute of Medical Sciences New Delhi, Medical Oncology, Dr. B.R.A. IRCH, New Delhi, India. ^[2] Radiodiagnosis, All India Institute of Medical Sciences New Delhi, New Delhi, India. ^[3] Radiodiagnosis, All India Institute of Medical Sciences New Delhi, Dr. B.R.A. IRCH, New Delhi, India. ^[4] Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India. amit.mehndiratta@keble.oxon.org.;Department of Biomedical Engineering, All India Institute of Medical Sciences New Delhi, New Delhi, India. amit.mehndiratta@keble.oxon.org. ^[5]

关键词 Computed tomography (CT)Computer-aided diagnosis (CAD)Convolutional neural networks (CNNs)Juxta-pleural nodules Lung parenchyma segmentation

主题词人类(Humans);肺(Lung);胸部(Thorax);图像处理, 计算机辅助(Image Processing, Computer-Assisted);体层摄影术, X线计算机(Tomography, X-Ray Computed)

DOI 10.1007/s11548-023-03010-0

PMID 37594684

发布时间 2024-08-22

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