Acknowledgement
This work was supported by the National Research Foundation of Korea (NRF-2021R1F1A1061440).
References
- C.R. Park, S.H. Kang, Y. Lee, Median modified wiener filter for improving the image quality of gamma camera images, Nucl. Eng. Technol. 52 (2020) 2328-2333. https://doi.org/10.1016/j.net.2020.03.022
- S.L. Pimlott, A. Sutherland, Molecular tracers for the PET and SPECT imaging of disease, Chem. Soc. Rev. 40 (2011) 149-162. https://doi.org/10.1039/B922628C
- A. Santra, R. Kumar, Brain perfusion single photon emission computed tomography in major psychiatric disorders: from basics to clinical practice, Indian J. Nucl. Med. 29 (2014) 210-221. https://doi.org/10.4103/0972-3919.142622
- V. Valotassiou, J. Malamitsi, J. Papatriantafyllou, E. Dardiotis, I. Tsougos, D. Psimadas, S. Alexiou, G. Hadjigeorgiou, P. Georgoulias, SPECT and PET imaging in Alzheimer's disease, Ann. Nucl. Med. 32 (2018) 583-593. https://doi.org/10.1007/s12149-018-1292-6
- T.A. Henderson, M.J. Lierop, M. McLean, J.M. Uszler, J.F. Thornton, Y.H. Siow, D.G. Pavel, J. Cardaci, P. Cohen, Functional neuroimaging in psychiatrydaiding in diagnosis and guiding treatment. What the American Psychiatric Association does not know, Front. Psychiatr. 15 (2020), https://doi.org/10.3389/fpsyt.2020.00276.
- S.C. Moore, K. Kouris, I. Cullum, Collimator design for single photon emission tomography, Eur. J. Nucl. Med. 19 (1992) 138-150.
- M.B. Tomas, P.V. Pugliese, G.G. Tronco, C. Love, C.J. Palestro, K.J. Nichols, Pinhole versus parallel-hole collimators for parathyroid imaging: an intraindividual comparison, J. Nucl. Med. Technol. 36 (2008) 189-194. https://doi.org/10.2967/jnmt.108.055640
- S. Kimiaei, S.A. Larsson, H. Jacobsson, Collimator design for improved spatial resolution in SPECT and planar scintigraphy, J. Nucl. Med. 37 (1996) 1417-1421.
- Y. Lee, H.J. Kim, Performance evaluation of a small CZT pixelated semiconductor gamma camera system with a newly designed stack-up parallelhole collimator, Nucl. Instrum. Methods Phys. Res. 794 (2015) 54-61. https://doi.org/10.1016/j.nima.2015.05.007
- Y. Lee, H.J. Ryu, S.W. Lee, S.J. Park, H.J. Kim, Comparison of ultra-highresolution parallel-hole collimator materials based on the CdTe pixelated semiconductor SPECT system, Nucl. Instrum. Methods Phys. Res. 713 (2013) 33-39. https://doi.org/10.1016/j.nima.2013.03.014
- B.M.W. Tsui, G.T. Gullberg, E.R. Edgerton, D.R. Gilland, J.R. Perry, W.H. Mccartney, Design and clinical utility of a fan beam collimator for SPECT imaging of the head, J. Nucl. Med. 27 (1986) 810-819.
- K.V. Audenhaege, R.V. Holen, S. Vandenberghe, C. Vanhove, S.D. Metzler, S.C. Moore, Review of SPECT collimator selection, optimization, and fabrication for clinical and preclinical imaging, Med. Phys. 42 (2015) 4796-4813. https://doi.org/10.1118/1.4927061
- K. Morita, A. Maebatake, R. Iwasaki, Y. Shiotsuki, K. Himuro, S. Baba, M. Sasaki, Evaluation of the reconstruction parameters of brain dopamine transporter SPECT images obtained by a fan beam collimator: a comparison with parallelhole Collimators, Asia-Oceania J. Nucl. Med. Biol. 6 (2018) 120-128.
- C.B. Lim, L.T. Chang, R.J. Jaszczak, Performance analysis of three camera configurations for single photon emission computed tomography, IEEE Trans. Nucl. Sci. 27 (2018) 559-568.
- S. Ozaki, A. Haga, E. Chao, C. Maurer, K. Nawa, T. Ohta, T. Nakamoto, Y. Nozawa, T. Magome, M. Nakano, K. Nakagawa, Fast statistical iterative reconstruction for mega-voltage computed tomography, J. Med. Invest. 67 (2020) 30-39. https://doi.org/10.2152/jmi.67.30
- C.R. Park, S.H. Kang, Y. Lee, Median modified wiener filter for improving the image quality of gamma camera images, Nucl. Eng. Technol. 52 (2020) 2328-2333. https://doi.org/10.1016/j.net.2020.03.022
- Y. Lee, Performance evaluation of noise reduction algorithm with median filter using improved thresholding method in pixelated semiconductor gamma camera system: a numerical simulation study, Nucl. Eng. Technol. 51 (2019) 439-443. https://doi.org/10.1016/j.net.2018.10.005
- M.Y. Jang, C.R. Park, S.H. Kang, Y. Lee, Experimental study of the fast non-local means noise reduction algorithm using the Hoffman 3D brain phantom in nuclear medicine SPECT image, Optik 224 (2020), 165440. https://doi.org/10.1016/j.ijleo.2020.165440
- K. Dabov, A. Foi, V. Katkovnik, K. Egiazarian, Image denoising by sparse 3-D transform-domain collaborative filtering, IEEE Trans. Image Process. 16 (2007) 2080-2095. https://doi.org/10.1109/TIP.2007.901238
- M. Lebrun, An analysis and implementation of the BM3D image denoising method, Image Process. Line 2 (2012) 175-213. https://doi.org/10.5201/ipol.2012.l-bm3d
- T. Zhao, J. Hoffman, M. McNitt-Gray, D. Ruan, Ultra-low-dose CT image denoising using modified BM3D scheme tailored to data statistics, Med. Phys. 23 (2018), https://doi.org/10.1002/mp.13252.
- V. Hanchate, K. Jochi, MRI denoising using BM3D equipped with noise invalidation denoising technique and VST for improved contrast, SN Appl. Sci. 2 (2020) 234. https://doi.org/10.1007/s42452-020-1937-7
- B. Song, Z. Duan, Y. Gao, T. Shao, Adaptive BM3D algorithm for image denoising using coefficient of variation, 22th Int. Conf. Info. Fusion (FUSION) (2019) 1-8.
- A. Mittal, A.K. Moorthy, A.C. Bovik, No-reference image quality assessment in the spatial domain, IEEE Trans. Image Process. 21 (2012) 4695-4708. https://doi.org/10.1109/TIP.2012.2214050
- S. Lee, Y. Lee, Performance evaluation of median-modified Wiener filter algorithm in high-resolution complementary metaleoxideesemiconductor radio-magnetic X-ray imaging system: an experimental study, Nucl. Instrum. Methods Phys. Res. 1010 (2021), 165509. https://doi.org/10.1016/j.nima.2021.165509
- J. Park, C.K. Kang, Y. Lee, Quantitative evaluation of the image quality using the fast nonlocal means denoising approach in diffusion-weighted magnetic resonance imaging with high b-value, J. Kor. Phys. Soc. 78 (2021) 244-250. https://doi.org/10.1007/s40042-020-00028-4
- M.M. Alqahtani, K.P. Willowson, C. Constable, R. Fulton, P.L. Kench, Optimization of 99mTc whole-body SPECT/CT image quality: a phantom study, J. Appl. Clin. Med. Phys. (2022), https://doi.org/10.1002/acm2.13528.
- Y. Lee, Improved quality using newly designed algorithms in gamma- and Xray fusion images with a photon counting CZT detector: combining the median modified Wiener filter and edge detection method, Optik 245 (2021), 167681. https://doi.org/10.1016/j.ijleo.2021.167681
- O.L. Kapucu, F. Nobili, A. Varrone, J. Booij, T.V. Borght, K. Nagren, J. Darcourt, K. Tatsch, K.J. Van Laere, EANM procedure guideline for brain perfusion SPECT using 99mTc-labelled radiopharmaceuticals, version 2, Eur. J. Nucl. Med. Mol. Imag. (2009), https://doi.org/10.1007/s00259-009-1266-y.
- H.S. Jeong, Y.A. Chung, J.S. Park, I.U. Song, Y. Yang, asLong- term efficacy of memantine in Parkinson's disease dementia: an 18-month prospective perfusion single photon emission computed tomography preliminary study, Dement. Neurocognitive Disord. 15 (2016) 43-48. https://doi.org/10.12779/dnd.2016.15.2.43
- J.J. van der Zande, M. Joling, I.G. Happach, C. Vriend, Ph Scheltens, J. Booij, A.W. Lemstra, Serotonergic deficits in dementia with Lewy bodies with concomitant Alzheimer's disease pathology: an 123I-FP-CIT SPECT study, Neuroimage: Clinic 25 (2020), 102062. https://doi.org/10.1016/j.nicl.2019.102062
- A. Sala, S.P. Caminiti, L. Presotto, A. Pilotto, C. Liguori, A. Chiaravalloti, V. Garibotto, G.B. Frisoni, M. D'Amelio, B. Paghera, O. Schillaci, N. Mercuri, A. Padovani, D. Perani, In vivo human molecular neuroimaging of dopaminergic vulnerability along the Alzheimer's disease phases, Alzheimer's Res. Ther. 13 (2021), https://doi.org/10.1186/s13195-021-00925-1.
- M. Decuyper, J. Maebe, R.V. Holen, S. Vandenberghe, Artificial intelligence with deep learning in nuclear medicine and radiology, EJNMMI Phys. 8 (2021), https://doi.org/10.1186/s40658-021-00426-y.
- K. Kim, Y. Lee, Improvement of signal and noise performance using single image super-resolution based on deep learning in single photon-emission computed tomography imaging system, Nucl. Eng. Technol. 53 (2021) 2341-2347. https://doi.org/10.1016/j.net.2021.01.011
- L.H. Hu, J. Betancur, T. Sharir, A.J. Einstein, S. Bokhari, M.B. Fish, T.D. Ruddy, P.A. Kaufmann, A.J. Sinusas, E.J. Miller, T.M. Bateman, S. Dorbala, M.D. Carli, G. Germano, F. Commandeur, J.X. Liang, Y. Otaki, B.K. Tamarappoo, D. Dey, D.S. Berman, P.J. Slomka, Machine learning predicts per-vessel early coronary revascularization after fast myocardial perfusion SPECT: results from multicentre REFINE SPECT registry, Eur. Heart J. Cardiovasc. Imag. 21 (2020) 549-559. https://doi.org/10.1093/ehjci/jez177
- J. Tsuchiya, K. Yokoyama, K. Yamagiwa, R. Watanabe, K. Kimura, M. Kishino, C. Chan, E. Asma, U. Tateishi, Deep learning-based image quality improvement of 18F-fluorodeoxyglucose positron emission tomography: a retrospective observational study, EJNMMI Phys. 8 (2021), https://doi.org/10.1186/s40658-021-00377-4.