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Weir AJ Klein SR Abrams G Adolphsen CE Akerlof C Alexander JP Alvarez M Amidei D Baden AR Ballam J Barish BC Barklow T Barnett BA Bartelt J Blockus D Bonvicini G Boyarski A Boyer J Brabson B Breakstone A Brom JM Bulos F Burchat PR Burke DL Butler F Calvino F Cence RJ Chapman J Cords D Coupal DP DeStaebler HC Dorfan DE Dorfan JM Drell PS Feldman GJ Fernandez E Field RC Ford WT Fordham C Frey R Fujino D Gan KK Gidal G Gladney L Glanzman T Gold MS Goldhaber G Green A Grosse-Wiesmann P Haggerty J 《Physical review D: Particles and fields》1990,41(5):1384-1388
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Wu DY Hayes K Perl ML Barklow T Boyarski A Burchat PR Burke DL Dorfan JM Feldman GJ Gladney L Hanson G Hollebeek RJ Innes WR Jaros JA Karlen D Klein SR Lankford AJ Larsen RR LeClaire BW Lockyer NS Lüth V Ong RA Richter B Riles K Yelton JM Abrams G Amidei D Baden AR Boyer J Butler F Gidal G Gold MS Goldhaber G Golding L Haggerty J Herrup D Juricic I Kadyk JA Levi ME Nelson ME Rowson PC Schellman H Schmidke WB Sheldon PD Trilling GH Wood DR Schaad T 《Physical review D: Particles and fields》1990,41(7):2339-2342
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Conventional multislice positron cameras reconstruct a three-dimensional distribution of a positron-emitting radioscope as a set of two-dimensional transverse sections. Consequently, annihilation photons which cross two or more planes are eliminated from the data. Such an approach makes efficient use of the emitted photon flux. A method is proposed which makes more efficient use of the available photons by including both oblique and transverse section in the reconstruction. The implementation of the method consists of centering a scaled convolution filter on each detected coincidence event line and backprojecting the filter values through the three-dimensional reconstruction volume. The final image is normalized to allow for the different number of oblique and transverse sections that contribute to each point in the imaging volume. The method has been evaluated using both simulated data and measured data obtained with a routing area detector positron camera. 相似文献
79.
An image-processing method called measurement-dependent filtering has been introduced to improve the SNR (signal-to-noise ratio) of selective images produced by various medical imaging systems. The basic algorithm involves the combination of the low-frequency information of the selective image with the high-frequency information of a nonselective image. A spatially variant control function modulates the amount of high frequency to be added at each point. A least-mean-square (LMS) control function formed from two basis images, namely the high-passed versions of the nonselective image (M(b)) and the selective image (S(b)), is introduced. The original algorithm is now viewed as a two-stage filtering method, including the low-pass filtering noise reduction and least squares filtering for the edge restoration. An appropriate linear transformation is used to convert the original basis images M(b) and S(b) into a new pair with orthogonal noise. This allows the implementation of the LMS and control function with practically obtainable a priori knowledge. 相似文献
80.
Ammar R Ball RC Banerjee S Bhat PC Bosetti P Bromberg C Canough GE Coffin T Dershem TO Dixon RL Fenker HC Ganguli SN Gensch U Girtler P Goshaw AT Grard F Gurtu A Hamilton C Henri VP Hernandez JJ Hrubec J Iori M Jones LW Kuhn D Knauss D Leedom ID Legros P Lemonne J Leutz H Liu X Malhotra PK Marraffino JM Mendez GE Miller R Naumann T Nguyen A Nowak H Pilette P Poirier J Poppleton A Raghavan R Rasner K Reucroft S Robertson WJ Roe BP Roth A Senko M Struczinski W Subramanian A Touboul MC Vonck B 《Physical review letters》1988,61(19):2185-2188