Kaiyan Li

University of Science and Technology of China

MedicineComputer ScienceEngineering

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile

0Author DataRank

Indexed papers

0in pilot corpus

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Papers

Driven by 5 papers. Top paper: “Assessing the Impact of Deep Neural Network-Based Image Denoising on Binary Signal Detection Tasks”.

Assessing the Impact of Deep Neural Network-Based Image Denoising on Binary Signal Detection Tasks

IEEE Transactions on Medical Imaging(2021)10.1109/tmi.2021.3076810

N/A

0DataRank · unranked

67 citations

Weimin Zhou, Hua Li, Mark A. Anastasio, Kaiyan Li

A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods

IEEE Transactions on Medical Imaging(2021)10.1109/tmi.2021.3135147

N/A

0DataRank · unranked

13 citations

Weimin Zhou, Hua Li, Mark A. Anastasio, Kaiyan Li

Application of learned ideal observers for estimating task-based performance bounds for computed imaging systems

Journal of Medical Imaging(2024)10.1117/1.jmi.11.2.026002

N/A

0DataRank · unranked

2 citations

Umberto Villa, Hua Li, Mark A. Anastasio, Kaiyan Li

Estimating task-based performance bounds for accelerated MRI image reconstruction methods by use of learned-ideal observers

PubMed(2025)10.1117/12.3047604

N/A

0DataRank · unranked

1 citations

Hua Li, Kyle J. Myers, Mark A. Anastasio, Kaiyan Li

Approximating the ideal observer for joint signal detection and estimation tasks by the use of Markov-Chain Monte Carlo with generative adversarial networks

Journal of Medical Imaging(2025)10.1117/1.jmi.12.5.051810

N/A

0DataRank · unranked

0 citations

Kaiyan Li, Weimin Zhou, Mark A. Anastasio, Dan Li