南方医科大学学报
南方醫科大學學報
남방의과대학학보
JOURNAL OF SOUTHERN MEDICAL UNIVERSITY
2015年
4期
474-480
,共7页
胡德斌%路利军%高园园%张后金%韩彦江%辜承慰%马建华
鬍德斌%路利軍%高園園%張後金%韓彥江%辜承慰%馬建華
호덕빈%로리군%고완완%장후금%한언강%고승위%마건화
PET%部分容积校正%去卷积%TV正则化
PET%部分容積校正%去捲積%TV正則化
PET%부분용적교정%거권적%TV정칙화
positron emission tomography%partial volume correction%deconvolution%total variation regularization
目的:提出全变分正则化去卷积方法并应用于PET图像部分容积校正。方法将全变分(toal variation, TV)引入到图像退化模型中,提出基于全变分正则化的Van Cittert(VC)和Richardson-Lucy(RL)去卷积方法。结果提出的方法分别应用于NCAT仿真数据、NEMA NU4-2008 IQ物理体模和肿瘤小鼠数据(均采用西门子小动物Inveon PET扫描得到)。相比于传统VC和RL去卷积方法,本文提出方法在仿真实验中校正图像有明显的去噪和保持边缘效果,同时在小鼠实验中肿瘤区域的活度值增加率为(10±1.8)%时,图像标准方差(standard deviation, SD)增加率分别从49.98%下降到14.26%和42.76%下降到4.70%。结论本方法能够在校正PET部分容积效应的同时有效抑制噪声增加,可望更为准确地诊断肿瘤。
目的:提齣全變分正則化去捲積方法併應用于PET圖像部分容積校正。方法將全變分(toal variation, TV)引入到圖像退化模型中,提齣基于全變分正則化的Van Cittert(VC)和Richardson-Lucy(RL)去捲積方法。結果提齣的方法分彆應用于NCAT倣真數據、NEMA NU4-2008 IQ物理體模和腫瘤小鼠數據(均採用西門子小動物Inveon PET掃描得到)。相比于傳統VC和RL去捲積方法,本文提齣方法在倣真實驗中校正圖像有明顯的去譟和保持邊緣效果,同時在小鼠實驗中腫瘤區域的活度值增加率為(10±1.8)%時,圖像標準方差(standard deviation, SD)增加率分彆從49.98%下降到14.26%和42.76%下降到4.70%。結論本方法能夠在校正PET部分容積效應的同時有效抑製譟聲增加,可望更為準確地診斷腫瘤。
목적:제출전변분정칙화거권적방법병응용우PET도상부분용적교정。방법장전변분(toal variation, TV)인입도도상퇴화모형중,제출기우전변분정칙화적Van Cittert(VC)화Richardson-Lucy(RL)거권적방법。결과제출적방법분별응용우NCAT방진수거、NEMA NU4-2008 IQ물리체모화종류소서수거(균채용서문자소동물Inveon PET소묘득도)。상비우전통VC화RL거권적방법,본문제출방법재방진실험중교정도상유명현적거조화보지변연효과,동시재소서실험중종류구역적활도치증가솔위(10±1.8)%시,도상표준방차(standard deviation, SD)증가솔분별종49.98%하강도14.26%화42.76%하강도4.70%。결론본방법능구재교정PET부분용적효응적동시유효억제조성증가,가망경위준학지진단종류。
Objective We propose a method using total variation (TV) regularization in deconvolution for partial volume correction in PET imaging. In the degraded image model, we used TV regularization procedure in Van Cittert (VC) and Richardson-Lucy (RL) deconvolution algorithms. These methods were tested in simulated NCAT images and images of NEMA NU4-2008 IQ phantom and tumor-bearing mouse scanned by Simens Invoen microPET. The simulated experiment and tumor-bearing mouse experiment showed that the algorithms using TV regularization provided superior qualitative and quantitative appearance compared with traditional VC and RL algorithms. When the mean intensity of the tumor increased by (10 ± 1.8)%, the SD increase percentage was decreased from 49.98%to 14.26%and from 42.76%to 4.70%, suggesting the efficiency of the proposed algorithms for reducing PVEs in PET.