1200 ノート 論文受付 2011 年 5 月 2 日 論文受理 2011 年 7 月 21 日 Code Nos. 131 251 532 1070 放射線技師教育用コーンビーム CT システムの開発 寺本篤司 1) 尾崎香帆 2) 宮下真梨子 3) 4) 大野智之津坂昌利 5) 藤田広志 6) 1) 小原健 1) 藤田保健衛生大学医療科学部放射線学科 2) 東名古屋画像診断クリニック 3) セントラル病院 4) 藤田保健衛生大学大学院保健学研究科 5) 名古屋大学医学部保健学科 6) 岐阜大学大学院医学系研究科知能イメージ情報分野 緒言 1970 computed tomography CT 1, 2 CT CT CT CT X 1 5 CT CT 3 5 CT Development of a Cone-beam CT System for Radiological Technologist Education Atsushi Teramoto, 1) Kaho Ozaki, 2) Mariko Miyashita, 3) Tomoyuki Ohno, 4) Masatoshi Tsuzaka, 5) Hiroshi Fujita, 6) and Ken Ohara 1) 1) Faculty of Radiological Technology, School of Health Sciences, Fujita Health University 2) East Nagoya Imaging Diagnosis Center 3) Central Hospital 4) Graduate School of Health Sciences, Fujita Health University 5) School of Health Sciences, Nagoya University 6) Department of Intelligent Image Information, Graduate School of Medicine, Gifu University Received May 2, 2011; Revision accepted July 21, 2011; Code Nos. 131 251 532 1070 Summary For radiological technologists, it is very important to understand the principle of computed tomography (CT) and CT artifacts derived from mechanical and electrical failure. In this study, a CT system for educating radiological technologists was developed. The system consisted of a cone-beam CT scanner and educational software. The cone-beam CT scanner has a simple structure, using a micro-focus X-ray tube and an indirect-conversion flat panel detector. For the educational software, we developed various educational functions of image reconstruction and reconstruction parameters as well as CT artifacts. In the experiments, the capabilities of the system were evaluated using an acrylic phantom. We verified that the system produced the expected results. Key words: computed tomography, cone-beam CT, image reconstruction, artifact, educational software 470-1192 1-98
CT 1201 CT 5 CT CT CT CT CT 1. 方法 CT 1-1 CT CT Fig. 1 CT X 5 μm 100 kv 100 μa X L7901 50 μm CsI CMOS 2366 2368 Fig. 1 Educational cone-beam CT system. flat panel detector; FPD C7942 0.002 X X source to image receptor distance; SID 500 mm source to object distance; SOD 50 mm 250 mm 2 10 5 25 μm 20 kg 2 personal computer PC X X 1-2 CT CT Feldkamp-Davis-Kress FDK 2011 9
1202 FDK 3, 4 1-2-1 FDK FDK Fig. 2 A B SOD SID x y z FDK θ n pn(u, v) qn(u, v) u, v q B 1 (,) u v = F ( P( ω, ω ) H( ω, ω )) 2 2 2 B + u + v n u v u v 1 Pn(ω u, ω v) pn(u, v) F 1 H(ω u, ω v) Ramp H(ω u, ω v)= ω u CT X qn(u, v) f(x, y, z) f(x, y, z) f( x, yz, ) = N 1 A qn( un( xy, ), vn ( x, y)) πn A xcosθ ysinθ 2 n= 1 2 N un(x, y), vn(x, y) B ( xsinθn ycos θn) un ( x, y) = A xcosθn ysinθn Bz Vn ( x, y) = A xcosθ ysinθ 3 un(x, y), vn(x, y) qn n n n n 2 Fig. 2 Coordinate system of cone-beam CT. The x-y-z space represents the volume, and the u-v plane represents a projection plane at the FPD. f(x, y, z) 1-2-2 CT 1 data acquisition system DAS CT CT Ramp Shepp-Logan 6 Microsoft Excel 1-3 CT
CT 1203 CT 5 1-3-1 1-3-2 1-3-3 1-3-2 DAS X DAS θ pn(u, v) 1-3-4 CT X z=0 X CT X Fig. 3 An example screen from the educational software. z X 5.85 X, 1-4 Microsoft Windows Visual C++2010 Fig. 3 FDK 1 Volume rendering; VR CT 2. 検証 2-1 2011 9
1204 Table 1 Scan parameters for experiments Parameter name (unit) Value X-ray tube voltage (kv) 80 X-ray tube current (μa) 125 X-ray source to image-receptor distance (mm) 500 X-ray source to object distance (mm) 250 Spatial resolution (μm) 25 Number of projections 360 Image integration time per projection (s) 1 Fig. 4 Slice images of the progressive image reconstruction for various ranges of projection angles. 20 mm Table 1 Ramp Core i7 2.8 GHz 4 G PC VR Osirix 7 2-2 2-2-1 Fig. 4 Fig. 5 VR 0 360 30 2-2-2 Fig. 6 4 8 12 16 32 360 VR 16 4 8 8 12 12 16 f 360 2-2-3 Fig. 7 a b Ramp
CT 1205 Fig. 5 Volume-rendered images of the progressive image reconstruction for various ranges of projection angles. Fig. 6 Slice images corresponding to the number of projections. The numbers denote the number of projections. 2-2-4 p(u, v) v Fig. 8 Fig. 9 a 0 90 25 Fig. 9 a 90 b c d Fig. 10 Fig. 7 Filtered and non-filtered back projection images. CT CT a 2011 9
1206 Fig. 10 CT images with streak artifacts. Fig. 8 Slice images of the progressive image reconstruction with ring artifacts for various ranges of projection angles. The white ring is the artifact. Fig. 11 CT images with shower artifacts. x-y Fig. 12 X 0 3 6 9 Fig. 13 Osirix multi planar reformation; MPR 0 Fig. 9 Volume-rendered images of the progressive image reconstruction with ring artifacts for various ranges of projection angles. The arrows point to the artifacts. b VR VR Fig. 11 θ 90 3. 考察 CT CT CT
CT 1207 Fig. 12 Projection images for various directions of X-ray incidence. Fig. 13 Sagittal MPR images reformed from reconstructed volume data for various directions of X-ray incidence. CT PC 3D VR CT VR Osirix VR VR CT CT CT CT 2011 9
1208 4. 結語 CT CT CT X CT 参考文献 1 Shepp LA, Kruskal JB. Computed tomography: the new medical X-ray technology. Am Math Mon 1978; 85: 420-439. 2 2010. 3 Feldkamp LA, Davis LC, Kress JW. Practical cone-beam algorithm. J Opt Soc Am A 1984; 1(6): 612-619. 4 2010: 679-686. 5 CT 2002. 6 2004: 968-972. 7 Rosset A, Spadola L, Ratib O. OsiriX: an open-source software for navigating in multidimensional DICOM images. J Digit Imaging 2004; 17(3): 205-216. 図表の説明 Fig. 1 Fig. 2 Fig. 3 Fig. 4 Fig. 5 Fig. 6 Fig. 7 Fig. 8 Fig. 9 Fig. 10 Fig. 11 Fig. 12 Fig. 13 CT a b CT x-y-z u-v FPD a f a f a f a b a d a d a b a b X a d X X a d X Table 1