PAN-FU KAO2026-10-162026-10-162003-01-01Pure ID: 15168041Pure UUID: 3afbf527-9969-48f5-9573-95d4b97c1707https://www.scopus.com/pages/publications/11844288325https://scholars.csmu.edu.tw/handle/123456789/22618We present an effective reconstruction algorithm of attenuation map from post-injection transmission scans. The post-injection transmission scan data are modeled as a collection of independent Poisson observations which consist of true transmission, cross-containment emission, and random coincidences. The mean values of cross-containment emission and random data are estimated by using Luk's approximation and Zaers' correction method, respectively. The reconstruction of the unknown attenuation map is also modeled using a Markov random field. A pre-conditioned conjugate gradient algorithm is then used to compute a maximum a posteriori estimate of the attenuation map by maximizing over the posterior density. Evaluations are conducted on clinical data collected from a CTI EXACT HR+ scanner. Experimental results show that the reconstructed results of attenuation map by the described reconstruction algorithm match well with theoretical values of soft tissue, bone and lung under 512 KeV photons.5enjournal article