GPT4LFS (generative pre-trained transformer 4 omni for lumbar foramina stenosis): enhancing lumbar foraminal stenosis image classification through large multimodal models.

Journal: The spine journal : official journal of the North American Spine Society
Published Date: Mar 27, 2025

Abstract

BACKGROUND CONTEXT: Lumbar foraminal stenosis (LFS) is a common spinal condition that requires accurate assessment. Current magnetic resonance imaging (MRI) reporting processes are often inefficient, and while deep learning has potential for improvement, challenges in generalization and interpretability limit its diagnostic effectiveness compared to physician expertise.

Authors

  • Elzat Elham-Yilizati Yilihamu
    Shandong University, Orthopedic Research Center of Shandong University & Advanced Medical Research Institute, Jinan 250000, China. Electronic address: elzatelham@mail.sdu.edu.cn.
  • Fan-Shuo Zeng
    Department of Rehabilitation of the Second Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan 250000, China. Electronic address: zfsdsg@126.com.
  • Jun Shang
    Renci Hospital of Xuzhou Medical University, Xuzhou 221000, China. Electronic address: drshjun@126.com.
  • Jin-Tao Yang
    Medical Research Department of Jiangsu Shiyu Intelligent Medical Technology Co., Nanjing 210000, China. Electronic address: jintao990729@gmail.com.
  • Hai Zhong
    The Second Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan 250000, China. Electronic address: 18753107255@163.com.
  • Shi-Qing Feng
    The Second Hospital of Shandong University, Cheeloo College of Medicine, Shandong University, Jinan 250000, China. Electronic address: shiqingfeng@sdu.edu.cn.

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