Transforming a low-count nuclear medicine image into a high-count image using Dynamic Stochastic Resonance

被引：0
|
作者：
Pandey, A. [1 ]
Kumar, S. [1 ]
Sharma, P. D. [1 ]
Patel, C. [1 ]
Kumar, R. [1 ]
机构：
[1] All India Inst Med Sci, New Delhi, India
来源：
EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING | 2023年 / 50卷 / SUPPL 1期
关键词：
D O I：
暂无
中图分类号：
R8 [特种医学]; R445 [影像诊断学];
学科分类号：
1002 ; 100207 ; 1009 ;
摘要：
EP-0717
引用
收藏
页码：S715 / S716
页数：2
相关论文
共 50 条
  • [11] Optimal Inversion of the Anscombe Transformation in Low-Count Poisson Image Denoising
    Makitalo, Markku
    Foi, Alessandro
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2011, 20 (01) : 99 - 109
  • [12] Nearly Exact Discrepancy Principle for Low-Count Poisson Image Restoration
    Bevilacqua, Francesca
    Lanza, Alessandro
    Pragliola, Monica
    Sgallari, Fiorella
    JOURNAL OF IMAGING, 2022, 8 (01)
  • [13] A new image enhancement technique (principle of stochastic resonance) in improving image quality of low count density image.
    Pandey, AK
    Pant, GS
    Sharma, PD
    Kumar, R
    Malhotra, A
    JOURNAL OF NUCLEAR MEDICINE, 2002, 43 (05) : 218P - 219P
  • [14] Low-count PET image reconstruction with Bayesian inference over a Deep Prior
    Carrillo, Hernan
    Millardet, Mael
    Carlier, Thomas
    Mateus, Diana
    MEDICAL IMAGING 2021: IMAGE PROCESSING, 2021, 11596
  • [15] Multimodal feature-guided diffusion model for low-count PET image denoising
    Lin, Gengjia
    Jin, Yuxi
    Huang, Zhenxing
    Chen, Zixiang
    Liu, Haizhou
    Zhou, Chao
    Zhang, Xu
    Fan, Wei
    Zhang, Na
    Liang, Dong
    Cao, Peng
    Hu, Zhanli
    MEDICAL PHYSICS, 2025,
  • [16] Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods
    Wang, Tonghe
    Lei, Yang
    Fu, Yabo
    Curran, Walter J.
    Liu, Tian
    Nye, Jonathon A.
    Yang, Xiaofeng
    PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS, 2020, 76 : 294 - 306
  • [17] Convolutional micro-networks for MR-guided low-count PET image processing
    da Costa-Luis, Casper O.
    Reader, Andrew J.
    2018 IEEE NUCLEAR SCIENCE SYMPOSIUM AND MEDICAL IMAGING CONFERENCE PROCEEDINGS (NSS/MIC), 2018,
  • [18] Application of trained Deep BCD-Net to iterative low-count PET image reconstruction
    Lim, Hongki
    Huang, Zhengyu
    Fessler, Jeffrey A.
    Dewaraja, Yuni K.
    Chun, Il Yong
    2018 IEEE NUCLEAR SCIENCE SYMPOSIUM AND MEDICAL IMAGING CONFERENCE PROCEEDINGS (NSS/MIC), 2018,
  • [19] What Numbers Don't Say: Immunogenetic Evidence Shows That High-Count MBL Resembles Rai 0 CLL While Low-Count MBL Does Not.
    Vardi, Anna
    Dagklis, Antonis
    Scarfo, Lydia
    Jelinek, Diane F.
    Newton, Darren J.
    Doughty, Chi
    Almeida, Julia
    Rodriguez-Caballero, Arancha
    Allgood, Sallie D.
    Lanasa, Mark C.
    Cortelezzi, Agostino
    Orlandi, Ester M.
    Veronese, Silvio
    Montillo, Marco
    Rawstron, Andy
    Shanafelt, Tait D.
    Orfao, Alberto
    Stamatopoulos, Kostas
    Ghia, Paolo
    BLOOD, 2012, 120 (21)
  • [20] Deep denoiser prior driven relaxed iterated Tikhonov method for low-count PET image restoration
    Chang, Weike
    D'Ascenzo, Nicola
    Antonecchia, Emanuele
    Li, Bingxuan
    Yang, Jigang
    Mu, Dengyun
    Li, Ang
    Xie, Qingguo
    PHYSICS IN MEDICINE AND BIOLOGY, 2024, 69 (16):
12345