Z
Ziping Liu
Researcher at Washington University in St. Louis
Publications - 14
Citations - 90
Ziping Liu is an academic researcher from Washington University in St. Louis. The author has contributed to research in topics: Voxel & Segmentation. The author has an hindex of 5, co-authored 14 publications receiving 54 citations. Previous affiliations of Ziping Liu include University of Rochester.
Papers
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Journal ArticleDOI
Objective Task-Based Evaluation of Artificial Intelligence-Based Medical Imaging Methods:: Framework, Strategies, and Role of the Physician.
Abhinav K. Jha,Kyle J. Myers,Nancy A. Obuchowski,Ziping Liu,Ashequr Rahman,Babak Saboury,Arman Rahmim,Barry A. Siegel +7 more
TL;DR: In this article, a framework for objective task-based evaluation of artificial intelligence methods for medical imaging applications is presented, with a focus on evaluating neural network-based methods for PET scans.
Proceedings ArticleDOI
Observer study-based evaluation of a stochastic and physics-based method to generate oncological PET images
Ziping Liu,Richard Laforest,Joyce Mhlanga,Tyler J. Fraum,Malak Itani,Farrokh Dehdashti,Barry A. Siegel,Abhinav K. Jha +7 more
TL;DR: A stochastic and physics-based method to generate realistic oncological two-dimensional PET images, where the ground-truth tumor properties are known, and extends upon a previously proposed approach to model intra-tumor heterogeneity using a lumpy object model.
Journal ArticleDOI
Validation of diffuse correlation spectroscopy sensitivity to nicotinamide-induced blood flow elevation in the murine hindlimb using the fluorescent microsphere technique.
TL;DR: The results of this study show that DCS is sensitive to nicotinamide-induced blood flow elevation in the murine left quadriceps femoris, suggesting that mouse models can be effectively employed to investigate the utility of DCS for various blood flow measurement applications.
Journal ArticleDOI
A Bayesian approach to tissue-fraction estimation for oncological PET segmentation.
Ziping Liu,Joyce Mhlanga,Richard Laforest,Paul-Robert Derenoncourt,Barry A. Siegel,Abhinav K. Jha +5 more
TL;DR: In this article, a Bayesian approach is proposed to estimate the posterior mean of the fractional volume that the tumor occupies within each image voxel, which is then used for tumor segmentation.
Posted Content
Fully automated 3D segmentation of dopamine transporter SPECT images using an estimation-based approach
TL;DR: The efficacy of the proposed estimation-based approach to segmentation of caudate, putamen, and globus pallidus in 3D DaT-SPECT images significantly outperformed all other considered segmentation methods and yielded accurate segmentation with dice similarity coefficients of ~ 0.80.