Deep learning-based MVIT-MLKA model for accurate classification of pancreatic lesions: a multicenter retrospective cohort study.

Journal: La Radiologia medica
PMID: 39832039

Abstract

BACKGROUND: Accurate differentiation between benign and malignant pancreatic lesions is critical for effective patient management. This study aimed to develop and validate a novel deep learning network using baseline computed tomography (CT) images to predict the classification of pancreatic lesions.

Authors

  • Hongfan Liao
    Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
  • Cheng Huang
    James H. Clark Center, Stanford University, Stanford, California, USA.
  • Chunhua Liu
  • Jiao Zhang
  • Fengming Tao
    Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
  • Haotian Liu
  • Hongwei Liang
    Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
  • Xiaoli Hu
    Department of Radiology, First Affiliated Hospital of Hunan University of Chinese Medicine, 410000 Changsha, China.
  • Yi Li
    Wuhan Zoncare Bio-Medical Electronics Co., Ltd, Wuhan, China.
  • Shanxiong Chen
  • Yongmei Li
    Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

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