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http://dx.doi.org/10.1016/j.net.2020.06.029

Application of sigmoidal optimization to reconstruct nuclear medicine image: Comparison with filtered back projection and iterative reconstruction method  

Shin, Han-Back (Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University, College of Medicine)
Kim, Moo-Sub (Department of Biomedical Engineering and Research Institute of Biomedical, Engineering, College of Medicine, Catholic University of Korea)
Law, Martin (Proton Therapy Pte Ltd)
Djeng, Shih-Kien (Proton Therapy Pte Ltd)
Choi, Min-Geon (Department of Biomedical Engineering and Research Institute of Biomedical, Engineering, College of Medicine, Catholic University of Korea)
Choi, Byung Wook (Department of Nuclear Medicine, Daegu Catholic University Medical Center, Catholic University of Daegu School of Medicine)
Kang, Sungmin (Department of Nuclear Medicine, Daegu Catholic University Medical Center, Catholic University of Daegu School of Medicine)
Kim, Dong-Wook (Department of Radiation Oncology, Yonsei Cancer Center, Yonsei University, College of Medicine)
Suh, Tae Suk (Department of Biomedical Engineering and Research Institute of Biomedical, Engineering, College of Medicine, Catholic University of Korea)
Yoon, Do-Kun (Department of Biomedical Engineering and Research Institute of Biomedical, Engineering, College of Medicine, Catholic University of Korea)
Publication Information
Nuclear Engineering and Technology / v.53, no.1, 2021 , pp. 258-265 More about this Journal
Abstract
High levels for noise and a loss of true signal make the quantitative interpretation of nuclear medicine (NM) images difficult. An application of profile optimization using a sigmoidal function in this study was used to acquire the NM images with high quality. And the images were acquired by using three kinds of reconstruction method using each same sinogram: a standard filtered back-projection (FBP), an iterative reconstruction (IR) technique, and the sigmoidal function profile optimization (SFPO). Comparison of image according to reconstruction method was performed to show a superiority of the SFPO for imaging. The images reconstructed by using the SFPO showed an average of 1.49 times and of 1.17 times better in contrast than the results obtained using the standard FBP and the IR technique, respectively. Higher signal to noise ratios were obtained as an average of 12.30 times and of 3.77 times than results obtained using the standard FBP and the IR technique, respectively. This study confirms that reconstruction with SFPO (vs FBP and vs IR) can lead to better lesion detectability and characterization with noise reduction. It can be developed for future reconstruction technique for the NM imaging.
Keywords
Sigmoid function; Profile optimization; PET; SPECT; Monte Carlo simulation;
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