Journal of Medical Physics
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ORIGINAL ARTICLE
Year : 2012  |  Volume : 37  |  Issue : 1  |  Page : 46-53

A new method to correct the attenuation map in simultaneous transmission/emission tomography using 153Gd/ 67Ga radioisotopes


1 Department of Nuclear Medicine, SGPGIMS, Lucknow, India
2 Department of Nuclear Medicine and Molecular Imaging Science, Institute of Nuclear Medicine, University College London, United Kingdom
3 Department of Physics, HNB University, Srinagar, India
4 Department of Radiotherapy and Radiation Medicine, IMS, BHU, Varanasi, India
5 Department of Radiotherapy, CSMMU, Lucknow, Uttar Pradesh, India
6 Department of Radiotherapy, SGPGIMS, Lucknow, India

Correspondence Address:
Subhash Chand Kheruka
Department of Nuclear Medicine, SGPGIMS, Lucknow - 226 014, Uttar Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0971-6203.92720

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Reconstruction of the tomographic images without attenuation correction can cause erroneously high count densities and reduced image contrast in low attenuation regions. In order to solve the problem of photon attenuation, one needs to know the attenuation coefficient for the individual patient being studied. Therefore, we made an attempt to correct the attenuation map in simultaneous transmission/emission tomography with 153 Gd/ 67 Ga using maximum likelihood method using the expectation maximization (ML-EM) algorithm to correct the transmission window for both the spillover and downscatter. Spillover fraction, scatter fraction and parameters for the scatter function (A, b and c) were determined experimentally and optimized using the optimization program written in IDL based on simplex theory. All measurements were performed on a Vertex gamma camera using the anthropomorphic thorax phantom for validation of data obtained by the proposed method. It was observed that without spillover and downscatter correction, the mean counts were 19.29 in liver and 26.90 in lung, whereas after after applying the corrections, the mean counts were reduced to 3.80 and 15.10 in liver and lung, respectively, which were close to true mean counts (liver 2.15 and lung 14.89). In this proposed method, we introduced the set of F t (spillover) and K t (downscatter) to account for the variations in projection pixels (f t and k t) with the density and thickness. The F t and K t were determined using the transmission data by an iterative process. The quantitative error was reduced by 98.0% for lung and 90.0% for liver when the corrected transmission images were obtained after the subtraction of spillover and downscatter fraction.


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