Automated Analysis of Standard Uptake Value for Torso FDG-PET Images
The purpose of this work was to develop an automated method to calculate the z-score of SUV for torso region on FDG-PET scans. The three dimensional distributions for the mean and the standard deviation values of SUV were stored in each volume to score the SUV in corresponding pixel position within unknown scans. The modeling methods is based on SPM approach using correction technique of Euler characteristic and Reset (Resolution element). We employed 193 normal cases to assemble the normal metabolism distribution of FDG. The physique were registered each other in a rectangular parallelepiped shape using affine transformation and Thin-Plate-Spline technique. The regions of the three organs were determined based on semi-automated procedure. Seventy-three abnormal spots were used to estimate the effectiveness of the scoring methods. As a result,the z-score images correctly represented that the z-scoresfor normal cases were between zeros to plus/minus 2 SD. Most of the z-scores of abnormal spots associated with cancer were lager than the upper of the SUV interval of normal organs.
FDG-PET SUV automated detection
Takeshi Hara Tetsuro Katafuchi Tatsunori Kobayashi Xiangrong Zhou Satoshi Itoh Hiroshi Fujita
Department of Intelligent Image Information,Graduate School of Medicine,Gifu University,Gifu,Japan Department of Radiological Technology,Gifu University of Medical Sciences,Gifu,Japan Department of Radiology,Daiyukai General Hospital,Aichi,Japan
国际会议
南宁
英文
277-279
2010-12-10（万方平台首次上网日期，不代表论文的发表时间）