7 citations · 8 across the 6 of their papers we have counts for
5 papers · 1 filter
NGSE-Corr: A technique for objective clinical evaluation of quantitative-imaging methods without a gold standard
Yan Liu, Ziping Liu, Zekun Li +4
Objective evaluation of quantitative-imaging (QI) methods based on how reliably they measure true values is important for clinical translation. Performing such evaluation with pati…
DEMIST: A deep-learning-based task-specific denoising approach for myocardial perfusion SPECT
Md Ashequr Rahman, Zitong Yu, Richard Laforest +3
There is an important need for methods to process myocardial perfusion imaging (MPI) SPECT images acquired at lower radiation dose and/or acquisition time such that the processed i…
Development and task-based evaluation of a scatter-window projection and deep learning-based transmission-less attenuation compensation method for myocardial perfusion SPECT
Zitong Yu, Md Ashequr Rahman, Craig K. Abbey +2
Attenuation compensation (AC) is beneficial for visual interpretation tasks in single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI). However, tradi…
Need for objective task-based evaluation of AI-based segmentation methods for quantitative PET
Ziping Liu, Joyce C. Mhlanga, Barry A. Siegel +1
Artificial intelligence (AI)-based methods are showing substantial promise in segmenting oncologic positron emission tomography (PET) images. For clinical translation of these meth…
No-gold-standard evaluation of quantitative imaging methods in the presence of correlated noise
Ziping Liu, Zekun Li, Joyce C. Mhlanga +2
Objective evaluation of quantitative imaging (QI) methods with patient data is highly desirable, but is hindered by the lack or unreliability of an available gold standard. To addr…