中国医学装备
中國醫學裝備
중국의학장비
China Medical Equipment
2015年
10期
18-22
,共5页
朱闻韬%李弘棣%吕中伟%汤雨%陈牧
硃聞韜%李弘棣%呂中偉%湯雨%陳牧
주문도%리홍체%려중위%탕우%진목
正电子发射断层摄影术%分辨率%重建%感兴趣区
正電子髮射斷層攝影術%分辨率%重建%感興趣區
정전자발사단층섭영술%분변솔%중건%감흥취구
Positron emission tomography%Resolution%Reconstruction%Region of interest
目的:建立一种PET成像中快速局域重建算法,对用户选择的感兴趣区域(ROI)进行局域的高精度重建,以快速获取局域高清PET图像。方法:使用较大像素(4.88 mm)对整个图像进行快速低分辨率重建,计算重建图像在ROI以外区域数据中的占比,再利用创新算法对用户选取的ROI做高分辨率重建。结果:对于实验中的NEMA IQ模体,当ROI图像的空间体积占全局图像1/8时,算法重建速度相比全局高分辨率重建提高约16倍(基于弦图重建)。同时,模拟和真实数据证实了算法定量的准确性,相比全局高清重建,重建图像各ROI均值的误差在1%以内。结论:快速局域重建算法为PET专家提供了一种可准确对自选区域以更高分辨率和更少时间进行重建的途径,在PET临床应用上具有广阔的潜在用途。
目的:建立一種PET成像中快速跼域重建算法,對用戶選擇的感興趣區域(ROI)進行跼域的高精度重建,以快速穫取跼域高清PET圖像。方法:使用較大像素(4.88 mm)對整箇圖像進行快速低分辨率重建,計算重建圖像在ROI以外區域數據中的佔比,再利用創新算法對用戶選取的ROI做高分辨率重建。結果:對于實驗中的NEMA IQ模體,噹ROI圖像的空間體積佔全跼圖像1/8時,算法重建速度相比全跼高分辨率重建提高約16倍(基于絃圖重建)。同時,模擬和真實數據證實瞭算法定量的準確性,相比全跼高清重建,重建圖像各ROI均值的誤差在1%以內。結論:快速跼域重建算法為PET專傢提供瞭一種可準確對自選區域以更高分辨率和更少時間進行重建的途徑,在PET臨床應用上具有廣闊的潛在用途。
목적:건립일충PET성상중쾌속국역중건산법,대용호선택적감흥취구역(ROI)진행국역적고정도중건,이쾌속획취국역고청PET도상。방법:사용교대상소(4.88 mm)대정개도상진행쾌속저분변솔중건,계산중건도상재ROI이외구역수거중적점비,재이용창신산법대용호선취적ROI주고분변솔중건。결과:대우실험중적NEMA IQ모체,당ROI도상적공간체적점전국도상1/8시,산법중건속도상비전국고분변솔중건제고약16배(기우현도중건)。동시,모의화진실수거증실료산법정량적준학성,상비전국고청중건,중건도상각ROI균치적오차재1%이내。결론:쾌속국역중건산법위PET전가제공료일충가준학대자선구역이경고분변솔화경소시간진행중건적도경,재PET림상응용상구유엄활적잠재용도。
Objective:The aim is to develop an efficient high resolution regional reconstruction algorithm for PET imaging. The high resolution reconstruction can be constraint to the user-selected region only, and therefore leads to significantly more efficient image reconstruction. Methods: The algorithm firstly uses large pixel size (e.g. 4.88 mm) to perform low resolution reconstruction for the whole image. After computing the contribution in data space apart from the user-selected region, an innovative high resolution reconstruction algorithm is performed for the user-selected region only. Results: The reconstruction speed is enhanced~16 times with sinogram-based reconstruction when the user-selected region includes approximately1/8 volume of the whole image. Simulation as well as clinical data demonstrate the accuracy of the algorithm, providing all ROI mean in reconstructed image differing <1% from the conventional reconstruction. Conclusion: This algorithm provides PET experts an approach to accurately reconstruct a user-selected region with high resolution and significantly less time. It is potentially of wide use in PET clinical applications.