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19 July 2024 Research on GAN-based MII-Net spine x-ray image restoration model in medical images
Jiaqi Song, Yanfeng Hu, Shuheng Wang, Qinyou Li, Yiming Liu, Junhao Huang, Xiaotong Shi, Lei Wang, Yibo Zhou, Bin Zhuge
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Proceedings Volume 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024); 132130Z (2024) https://doi.org/10.1117/12.3035461
Event: International Conference on Image Processing and Artificial Intelligence (ICIPAl2024), 2024, Suzhou, China
Abstract
In the domain of spine 2D/3D medical image registration, the use of a registration plate is essential for assisting the registration process. To enhance registration accuracy, it is crucial to repair the registration plate images contained within X-ray images. Addressing this challenge, we introduce a GAN-based Mask Inpainting Image Net (MII-Net) model specifically designed for repairing orthopedic locator images in spinal X-ray photographs. This model leverages the Fast Fourier Convolution to reconstruct the image receptive field and employs a strategy that generates a 50% occlusion mask image for training the repair network. The network was trained using custom training and validation sets, and its repair performance was assessed using the FID and LPIPS indices. Post-training results indicated that the model achieved an FID index of 1.45 and an LPIPS index of 0.12 in the validation set, with the SSIM index reaching 0.95. The MII-Net model, powered by GAN technology, guarantees high-quality image repair outcomes, enabling precise repairs of registration plate images in spinal X-ray images. When compared to other models using the same dataset, the MII-Net model surpasses them in terms of both the FID and LPIPS indices.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Jiaqi Song, Yanfeng Hu, Shuheng Wang, Qinyou Li, Yiming Liu, Junhao Huang, Xiaotong Shi, Lei Wang, Yibo Zhou, and Bin Zhuge "Research on GAN-based MII-Net spine x-ray image restoration model in medical images", Proc. SPIE 13213, International Conference on Image Processing and Artificial Intelligence (ICIPAl 2024), 132130Z (19 July 2024); https://doi.org/10.1117/12.3035461
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KEYWORDS
X-rays
X-ray imaging
Image restoration
Spine
Image quality
Convolution
Medical imaging
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