解放军医学院学报2025，Vol.46Issue(10)：982-987,6.DOI:10.12435/j.issn.2095-5227.24113002
面向医学影像细微特征的低损耗压缩编码算法的研究与应用
Research and application of low-loss compression coding algorithms for fine features in medical imaging
摘要
Abstract
Background Current medical image compression techniques primarily optimize for mean squared error(MSE),which does not fully capture human subjective perception of image quality and often fail to preserve the structural features essential for clinical diagnosis.Objective To propose a low-loss compression coding algorithm for subtle features in medical images,aiming to reduce transmission bandwidth without compromising subjective image quality.Methods CT image sequences from 14 orthopedic surgeries at Chinese PLA General Hospital were collected in this study.Firstly,the Structural Similarity Index(SSIM)was reconstructed based on key visual features of medical images,including brightness,contrast,and detail texture,with the brightness factor set to α=1.15 and the contrast/structure factors set to β=γ=0.95.Subsequently,a relationship between the SSIM and MSE was established based on the linear distortion model and the law of large numbers.Then,1/SSIM was employed as a distortion metric,and an SSIM-based distortion measure suitable for rate-distortion optimization(RDO)was constructed.On this basis,a SSIM-based rate-distortion optimization framework was developed by minimizing the distortion metric under a given target bitrate constraint.Finally,the proposed method was implemented on the x264 platform,and its rate-distortion performance was compared with that of the standard encoder to verify its advantages.Results Compared to the standard x264 encoder,our approach achieved an average rate-distortion gain of-5.2%under constant quantization parameter and-4.8%under constant quality factor.In terms of subjective quality,the SSIM of the encoded images remained above 0.95,with an average bitrate reduction of 372 kbps.Furthermore,no increase in computational complexity or encoding time was observed.Conclusion The proposed method effectively preserves the high perceptual quality of medical images while maintaining computational efficiency,offering a superior compression solution for medical image transmission.关键词
医学影像/视频压缩/率失真优化/主观质量评价/结构相似度指数/感官质量/远程医学Key words
medical imaging/video compression/rate-distortion optimization/subjective quality assessment/SSIM/perceptual quality/telemedicine分类
医药卫生引用本文复制引用
王瑞青,何昆仑,陈华,曹德森,栗嘉楠,马骏..面向医学影像细微特征的低损耗压缩编码算法的研究与应用[J].解放军医学院学报,2025,46(10):982-987,6.基金项目
科技创新2030-新一代人工智能重大项目(2021ZD0140410) （2021ZD0140410）
