“高分辨率PET動(dòng)態(tài)成像與相關(guān)參數(shù)估計(jì)”中期報(bào)告

劉華鋒 馬建華

摘要：按照工作計(jì)劃及預(yù)期目標(biāo)，我們切實(shí)把握PET成像中的兩大關(guān)鍵問題：放射性濃度重構(gòu)和參數(shù)圖像重建。兩年來，在國家目標(biāo)和學(xué)科發(fā)展趨勢(shì)的導(dǎo)引下，立足充分把握成像組織生理模型基礎(chǔ)上，沿襲經(jīng)典PET重建與創(chuàng)新狀態(tài)空間重建兩種技術(shù)路線，采用Monte Carlo仿真、動(dòng)物模型、真實(shí)人體數(shù)據(jù)三種驗(yàn)證手段，發(fā)展與提出了一系列PET成像新方法。

關(guān)鍵詞：正電子斷層成像；圖像重建；狀態(tài)空間法

Abstract：Pioneered the state space framework for functional molecular image reconstruction， where the proposed strategy formulates the organ activity distribution through tracer kinetics models and the photon-counting measurements through observation equations. This paradigm undertakes the uncertainties on both the imaging system model and the measurement data model； and it is capable of unifying the dynamic and the static reconstruction problems into a general framework， and can simultaneously estimate the tissue attenuation map and activity map. This series of efforts have been extremely well received by the international community， and have been presented at a number of top conferences such as MICCAI， ICIP and published/accepted by top journals such as TBME， TMI， PMB.

Keywords：PET； Image Reconstruction； State space method

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