中华放射医学与防护杂志
中華放射醫學與防護雜誌
중화방사의학여방호잡지
Chinese Journal of Radiological Medicine and Protection
2009年
1期
106-108
,共3页
婴幼儿%多重分形谱%体层摄影术%X线计算机
嬰幼兒%多重分形譜%體層攝影術%X線計算機
영유인%다중분형보%체층섭영술%X선계산궤
Infants%Muiltifractal spectrum%Tomogaphy%X-ray computed
目的 对婴幼儿脑的64层CT低分辨率扫描图像进行分形计算及优化分析.方法 将Toshiba Aquilion 64层CT使用10 mAs扫描婴幼儿脑的CT成像原始数据输入Matlab7.1图像工具箱,进行多重分形谱分析和实验性图像降噪,并与常规低剂量扫描50 mAs组图像质量进行对比.结果 10 mAs原始图像的严重噪声导致医学诊断价值丧失,使用多重分形模型降噪后的图像具有良好的图像细节保持特性及良好的细节保持特性,虽然图像质量评分仍远不如常规剂量图像,但与原始噪声图像比较,其差异有统计学意义(F=38.85,P<0.01),表明经分形模型降噪优化后的图像可以基本满足临床诊断.结论 多重分形谱降噪可用于低剂量低分辨率CT图像的优化,能提高病变检出敏感性的对比度/噪声比,进一步研究应用有望大幅度减少婴幼儿CT扫描的辐射剂量.
目的 對嬰幼兒腦的64層CT低分辨率掃描圖像進行分形計算及優化分析.方法 將Toshiba Aquilion 64層CT使用10 mAs掃描嬰幼兒腦的CT成像原始數據輸入Matlab7.1圖像工具箱,進行多重分形譜分析和實驗性圖像降譟,併與常規低劑量掃描50 mAs組圖像質量進行對比.結果 10 mAs原始圖像的嚴重譟聲導緻醫學診斷價值喪失,使用多重分形模型降譟後的圖像具有良好的圖像細節保持特性及良好的細節保持特性,雖然圖像質量評分仍遠不如常規劑量圖像,但與原始譟聲圖像比較,其差異有統計學意義(F=38.85,P<0.01),錶明經分形模型降譟優化後的圖像可以基本滿足臨床診斷.結論 多重分形譜降譟可用于低劑量低分辨率CT圖像的優化,能提高病變檢齣敏感性的對比度/譟聲比,進一步研究應用有望大幅度減少嬰幼兒CT掃描的輻射劑量.
목적 대영유인뇌적64층CT저분변솔소묘도상진행분형계산급우화분석.방법 장Toshiba Aquilion 64층CT사용10 mAs소묘영유인뇌적CT성상원시수거수입Matlab7.1도상공구상,진행다중분형보분석화실험성도상강조,병여상규저제량소묘50 mAs조도상질량진행대비.결과 10 mAs원시도상적엄중조성도치의학진단개치상실,사용다중분형모형강조후적도상구유량호적도상세절보지특성급량호적세절보지특성,수연도상질량평분잉원불여상규제량도상,단여원시조성도상비교,기차이유통계학의의(F=38.85,P<0.01),표명경분형모형강조우화후적도상가이기본만족림상진단.결론 다중분형보강조가용우저제량저분변솔CT도상적우화,능제고병변검출민감성적대비도/조성비,진일보연구응용유망대폭도감소영유인CT소묘적복사제량.
Objective To analyze scanned image optimization based on the multifractal soectrum and image fractal algorithm of 64-slice spiral CT in brain of infant. Methods The image data of Toshiba Aquilion 64-slice CT scanning using 10 mAs were imported to image processing toolboxs of Matlab 7.1. The evaluation of muhifractal spectrum and image denosing were performed, and compared with image quality of conventional low-dose CT using 50 mAs. Results The low-contrast scanned image used 10 mAs is the valueless medical image because of serious noise. Image denoise based on the fractal model had superior characteristic of image detail preserving and better contrast-to-noise ratio(CNR). There existed a group difference in the score of image quality between the rude imaging noise and optimized image based on the muhffraetal spectrum algorithm, though the score was still significantly lower than the normal dosage scanned image(F = 38.85, P < 0.01). The group difference was also manifested the image quality of infants can achieve basieaUy the request of clinical diagnosis by suitable model denoising algorithm. Conclusions Image denoising based on the multifraetal spectrum model can be used on the low-dose and low-contrast CT image optimization. It improved the CNR of the pathological region. The radiation dose of CT scanning in infants would be declined significantly by its further application in the future.
