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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 4

Dual-channel translation Fusion network for reconstructing three-dimensional spinal models from biplane radiographs

Ling Jianhang
Zhang Junhua
School of Information, Yunnan University, Kunming 650000, China
DOI: 10.19734/j.issn.1001-3695.2024.07.0272

Abstract

Understanding the three-dimensional structure of the spine in a standing posture is crucial for effective scoliosis treatment. Traditional CT imaging does not meet the requirements for standing posture assessments and is challenged by high radiation and limited applicability to certain population groups. This study introduced a convolutional neural network called 2XR3DS-Net, which reconstructs the three-dimensional spinal model from biplane radiographs. The method incorporated a residual network combined with a channel attention mechanism into the dual-channel convolutional network, enhancing the capability to extract spinal information from radiographs and improving the overall quality of the reconstruction. The study also developed a transfer fusion module to resolve the issue of inconsistent two-dimensional feature semantics from different radiographs, thereby enhancing the detail of the reconstructed object. The reconstruction process used a three-dimensional deconvolution module with shared channel parameters, which reduced the number of model parameters and significantly decreased the training time. The three-dimensional spine models that 2XR3DS-Net reconstructed from 17 different test sets achieved averages of 3.40 mm in Hausdorff distance, 0.55 mm in average surface distance, and 0.60 in 3D intersection over union ratio. The reconstruction results outperformed other methods in terms of Hausdorff distance, average surface distance, and 3D intersection over union ratio. The experimental results demonstrate the effectiveness of the proposed method.

Foundation Support

国家自然科学基金资助项目(62063034,61841112)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.07.0272
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 4

Publish History

[2024-10-14] Accepted Paper

Cite This Article

凌健航, 张俊华. 双通道转义融合网络实现双平面X线片重建脊柱三维模型 [J]. 计算机应用研究, 2025, 42 (4). (2024-12-31). https://doi.org/10.19734/j.issn.1001-3695.2024.07.0272. (Ling Jianhang, Zhang Junhua. Dual-channel translation Fusion network for reconstructing three-dimensional spinal models from biplane radiographs [J]. Application Research of Computers, 2025, 42 (4). (2024-12-31). https://doi.org/10.19734/j.issn.1001-3695.2024.07.0272. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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