Neural network-based position estimators for PET detectors using monolithic LSO blocks

التفاصيل البيبلوغرافية
العنوان: Neural network-based position estimators for PET detectors using monolithic LSO blocks
المؤلفون: Yibao Wu, C. Lemaitre, O. Devroede, S. Tavernier, M. Krieguer, S. Leonard, P. Bruyndonckx
المصدر: IEEE Transactions on Nuclear Science. 51:2520-2525
بيانات النشر: Institute of Electrical and Electronics Engineers (IEEE), 2004.
سنة النشر: 2004
مصطلحات موضوعية: Physics, Nuclear and High Energy Physics, Photon, Tomographic reconstruction, business.industry, Detector, Photodetector, Scintillator, Avalanche photodiode, Full width at half maximum, Optics, Nuclear Energy and Engineering, Perpendicular, Electrical and Electronic Engineering, business
الوصف: The impinging position of a 511 keV photon onto a continuous scintillator can be obtained from the light distribution measured by a pixelated photodetector such as avalanche photodiode (APD) arrays. This information is extracted using neural networks trained for events with a particular incidence angle. Using a 20/spl times/10/spl times/10 mm block of lutetium oxyorthosilicate mounted onto a S8550 Hamamatsu APD matrix we achieved an intrinsic resolution of 1.9 mm full-width at half-maximum (FWHM) for perpendicular incident photons and 2.6 mm FWHM at a 40/spl deg/ incidence angle. A possible implementation for tomographic imaging is presented.
تدمد: 0018-9499
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_________::ca1fd34ba36ae534cfe8b7ae831df3bfTest
https://doi.org/10.1109/tns.2004.835782Test
حقوق: CLOSED
رقم الانضمام: edsair.doi...........ca1fd34ba36ae534cfe8b7ae831df3bf
قاعدة البيانات: OpenAIRE