CAJ | 학술논문

随着医院数字化医疗进程的加快,医学影像的数据量日益增大,医学影像资料的存储空间和获取速度受到很大的限制。文章在研究主流字典学习算法基础上,提出使用不同尺度的 MOD、K-SVD、ILS-DLA、RLS-DLA 字典算法对 DI-COM 图像进行压缩存储,以及恢复再现的方法。与经典的 JPEG 和 JPEG2000压缩算法相比,字典学习算法压缩和恢复效果较好,特别是采用较小尺度的字典时,压缩效果更为突出：当压缩比为20时,采用4×4尺度的 RLS-DLA 字典,论文算法的峰值信噪比(PSNR)较 JPEG 算法高出7.8 dB,比 JPEG2000算法高出1 dB。
수착의원수자화의료진정적가쾌,의학영상적수거량일익증대,의학영상자료적존저공간화획취속도수도흔대적한제。문장재연구주류자전학습산법기출상,제출사용불동척도적 MOD、K-SVD、ILS-DLA、RLS-DLA 자전산법대 DI-COM 도상진행압축존저,이급회복재현적방법。여경전적 JPEG 화 JPEG2000압축산법상비,자전학습산법압축화회복효과교호,특별시채용교소척도적자전시,압축효과경위돌출：당압축비위20시,채용4×4척도적 RLS-DLA 자전,논문산법적봉치신조비(PSNR)교 JPEG 산법고출7.8 dB,비 JPEG2000산법고출1 dB。
With the accelerated developing of hospital digital medical,the amount of medical imaging data grows dramatically,which affects the data storage space and access speed.This paper proposes a new design which uses different scales dictionaries of MOD,K-SVD,ILS-DLA,RLS-DLA for digital imaging and communications in medicine (DICOM)image compression storage and restore methods based on dictionary learning.Compared with the traditional algorithms JPEG and JPEG2000,the pro-posed method has better performance,especially when the dictionary scale is smaller.For example, when the compression ratio is 20,using 4×4 dictionary scale,the peak signal to noise ratio (PSNR) of the proposed method is 7.8 dB higher than that of JPEG,and 1dB than JPEG2000.