High precision localization of pulmonary nodules on chest CT utilizing axial slice number labels.

Journal: BMC medical imaging
Published Date: Apr 9, 2021

Abstract

BACKGROUND: Reidentification of prior nodules for temporal comparison is an important but time-consuming step in lung cancer screening. We develop and evaluate an automated nodule detector that utilizes the axial-slice number of nodules found in radiology reports to generate high precision nodule predictions.

Authors

  • Yeshwant Reddy Chillakuru
    Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143, USA.
  • Kyle Kranen
    Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143, USA.
  • Vishnu Doppalapudi
    Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143, USA.
  • Zhangyuan Xiong
    Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143, USA.
  • Letian Fu
    Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143, USA.
  • Aarash Heydari
    Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143, USA.
  • Aditya Sheth
    Department of Radiology and Biomedical Imaging, University of California San Francisco, 505 Parnassus Ave, San Francisco, CA, 94143, USA.
  • Youngho Seo
    Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.
  • Thienkhai Vu
    Radiology & Biomedical Imaging, UCSF Medical Center, 505 Parnassus Ave, San Francisco, CA, 94158, USA.
  • Jae Ho Sohn
    Radiology & Biomedical Imaging, UCSF Medical Center, 505 Parnassus Ave, San Francisco, CA, 94158, USA. sohn87@gmail.com.

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