Computer Science

Computer Science ›› 2025, Vol. 52 ›› Issue (11A): 241100152-7.doi: 10.11896/jsjkx.241100152

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Optimization of 3D Reconstruction Algorithm Based on X-ray of Lower Limb Bone

WANG Baohui1, DU Hui2, ZHANG Yuan1   

  1. 1 School of Software,Beihang University,Beijing 100191,China
    2 Beijing Jishuitan Hospital,Capital Medical University,Beijing 100032,China
  • Online:2025-11-15 Published:2025-11-10
  • Supported by:
    Beijing Natural Science Foundation-Haidian Original Innovation Joint Fund Project(L222059).

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Abstract: In clinical practice,bone malformations of the lower limb are common and difficult to treat in orthopedic medicine.Doctors usually rely on anteroposterior and lateral X-rays to judge the degree of malformations in the weight-bearing position,but this process is highly dependent on the professional level and experience level of doctors.Although three-dimensional CT imaging technology exists,it cannot meet the diagnostic requirements well due to the difference between patients who need to lie flat and standing weight-bearing position during CT imaging.Therefore,it is essential to create a more intuitive and accurate display of the lower limb bone malformation model.This will not only simplify the work of doctors,but also improve the accuracy of diagnoses and help them develop more effective treatment plans.This paper proposes a model based on PSSobel-X2CTGAN model,and on the basis of this model,Transformer mechanism is added to the reshape module.In addition,CycleGAN is used for data enhancement in the preparation of data sets.After validation of the data sets in the original paper,the experimental results clearly show that the structural similarity values of the model reaches 79.51% and 56.32% on the CT-PELVIC and SKI10 data sets,respectively,while the values of the original model are only 77.49% and 49.53%,indicating a significant improvement.

Key words: Load position, Three-dimensional reconstruction, Transformer, CycleGAN, Correction of lower limb deformity

CLC Number: 

  • TP391
[1]YE R W,WANG B H.Research on Lower Limb X-ray 3D Reconstruction Algorithm Based on Generative Adversarial Network[J].Computer Science,2024,51(S2):232-238.
[2]SHEPP L A,VARDI Y.Maximum Likelihood Reconstructionfor Emission Tomography[J].IEEE Transactions on Medical Imaging,1983,1:113-122.
[3]LUSTIG M,DONOHO D L,PAULY J M.Sparse MRI:The application of compressed sensing for rapid MR imaging[J].Magnetic Resonance in Medicine,2007,58(6):1182-1195.
[4]HERMAN G T.Fundamentals of Computerized Tomography:Image Reconstruction from Projections[C]//Advances in Pattern Recognition.2009.
[5]LAMECKER H,WENCKEBACH T H,HEGE H.Atlas-based 3D-Shape Reconstruction from X-Ray Images[C]//18th International Conference on Pattern Recognition(ICPR’06).2006:371-374.
[6]SERRADELL E,ROMERO A,LETA R,et al.Simultaneouscorrespondence and non-rigid 3D reconstruction of the coronary tree from single X-ray images[C]//2011 International Confe-rence on Computer Vision.2011:850- 857.
[7]EIGEN D,PUHRSCH C,FERGUS R.Depth Map Prediction from a Single Image using a Multi-Scale Deep Network[C]//NIPS.2014.
[8]HENZLER P,RASCHE V,ROPINSKI T,et al.Single-imageTomography:3D Volumes from 2D X-Rays[J].arXiv:1710.04867,2017.
[9]YING X,GUO H,MA K,et al.X2CT-GAN:Reconstructing CT From Biplanar X-Rays With Generative Adversarial Networks[C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR).2019:10611-10620.
[10]WÜRFL T,GHESU F C,CHRISTLEIN V,et al.Deep Learning Computed Tomography[C]//International Conference on Medical Image Computing and Computer-Assisted Intervention.2016.
[11]MAGNOR M A,KINDLMANN G L,DURIC N,et al.Con-strained inverse volume rendering for planetary nebulae[J].IEEE Visualization,2004,2004:83-90.
[12]SHI W,CABALLERO J,HUSZÁR F,et al.Real-Time SingleImage and Video Super- Resolution Using an Efficient Sub-Pixel Convolutional Neural Network[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition(CVPR).2016:1874-1883.
[13]MAO X,LI Q,XIE H,et al.Least Squares Generative Adversarial Networks[C]//2017 IEEE International Conference on Computer Vision(ICCV).2016:2813-2821.
[14]YU B,ZHOU L,WANG L,et al.Ea-GANs:Edge-Aware Ge-nerative Adversarial Networks for Cross-Modality MR Image Synthesis[J]IEEE Transactions on Medical Imaging,2019,38:1750-1762.
[15]BAHNER M L,DEBUS J,ZABEL A,et al.Digitally reconstructed radiographs from abdominal CT scans as a new tool for radiotherapy planning[J].Investigative Radiology,1999,34(10):643-647.
[16]LIU P,HAN H,DU Y,et al.Deep learning to segment pelvic bones:large-scale CT datasets and baseline models[J].International Journal of Computer Assisted Radiology and Surgery,2020,16:749-756.
[17]HEIMANN T,MORRISON B,STYNER M A,et al.Segmentation of Knee Images:A Grand Challenge[C]//MICCAI Workshop on Medical Image Analysis for the Clinic.2010:207-214.
[18]CARION N,MASSA F,SYNNAEVE G,et al.End-to-end object detection with transformers[C]//European Conference on Computer Vision.Springer,2020:213-222.
[19]CHEN H,GU J,ZHANG Z.Attention in attention network for image super-resolution[J].arXiv:2104.09497,2021.
[20]ZHU J,PARK T,ISOLA P,et al.Unpaired Image-to-ImageTranslation Using Cycle-Consistent Adversarial Networks[C]//IEEE International Conference on Computer Vision(ICCV).2017:2242-2251.
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