Ultrasound-based deep learning radiomics model for differentiating benign, borderline, and malignant ovarian tumours: a multi-class classification exploratory study.

Journal: BMC medical imaging
Published Date: Apr 15, 2024

Abstract

BACKGROUND: Accurate preoperative identification of ovarian tumour subtypes is imperative for patients as it enables physicians to custom-tailor precise and individualized management strategies. So, we have developed an ultrasound (US)-based multiclass prediction algorithm for differentiating between benign, borderline, and malignant ovarian tumours.

Authors

  • Yangchun Du
    Department of Ultrasound, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Qingxiu District, 530021, Nanning, China.
  • Wenwen Guo
    Department of Pathology, The People's Hospital of Guangxi Zhuang Autonomous Region & Guangxi Academy of Medical Sciences, No.6 Taoyuan Road, Qingxiu District, 530021, Nanning, China.
  • Yanju Xiao
    Department of Ultrasound, The People's Hospital of Guangxi Zhuang Autonomous Region & Guangxi Academy of Medical Sciences, No.6 Taoyuan Road, Qingxiu District, 530021, Nanning, China.
  • Haining Chen
    Department of Orthopedics, Affiliated Hospital of Jiangsu University, Zhenjiang Jiangsu, 212001, P.R.China.
  • Jinxiu Yao
    Department of Ultrasound, The People's Hospital of Guangxi Zhuang Autonomous Region & Guangxi Academy of Medical Sciences, No.6 Taoyuan Road, Qingxiu District, 530021, Nanning, China.
  • Ji Wu
    Department of Urology, Nanchong Central Hospital, Nanchong, Sichuan, China.

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