Quande Liu

2.0k total citations · 1 hit paper
10 papers, 753 citations indexed

About

Quande Liu is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Quande Liu has authored 10 papers receiving a total of 753 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Artificial Intelligence and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Quande Liu's work include COVID-19 diagnosis using AI (4 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Cardiac Imaging and Diagnostics (2 papers). Quande Liu is often cited by papers focused on COVID-19 diagnosis using AI (4 papers), Domain Adaptation and Few-Shot Learning (4 papers) and Cardiac Imaging and Diagnostics (2 papers). Quande Liu collaborates with scholars based in Hong Kong, China and Bangladesh. Quande Liu's co-authors include Qi Dou, Pheng‐Ann Heng, Cheng Chen, Jing Qin, Ben Glocker, Yueming Jin, Luyang Luo, Xi Wang, Lequan Yu and Hao Chen and has published in prestigious journals such as IEEE Transactions on Medical Imaging, IEEE Journal of Biomedical and Health Informatics and Frontiers in Cardiovascular Medicine.

In The Last Decade

Quande Liu

9 papers receiving 745 citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space

2021 292 citations Quande Liu, Cheng Chen et al. The HKU Scholars Hub (University of Hong Kong) profile →

Peers

Countries citing papers authored by Quande Liu

Since Specialization

Citations

This map shows the geographic impact of Quande Liu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Quande Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quande Liu more than expected).

Fields of papers citing papers by Quande Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Quande Liu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Quande Liu. The network helps show where Quande Liu may publish in the future.

Co-authorship network of co-authors of Quande Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Quande Liu. A scholar is included among the top collaborators of Quande Liu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Quande Liu. Quande Liu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

#	Work	Indexed citations
1	Context as Memory: Scene-Consistent Interactive Long Video Generation with Memory Retrieval 2025 ·Jiwen Yu, (unknown), (unknown), Quande Liu, Xintao Wang, Pengfei Wan, (unknown), Xihui Liu	0
2	The value of myocardial work in the estimation of left ventricular systolic function in patients with coronary microvascular disease: A study based on adenosine stress echocardiography 2023 ·Frontiers in Cardiovascular Medicine ·Quande Liu, (unknown), (unknown), Mingjun Xu, (unknown), Yu Zhang, Mengmeng Li, Mei Zhang	5
3	DLTTA: Dynamic Learning Rate for Test-Time Adaptation on Cross-Domain Medical Images 2022 ·IEEE Transactions on Medical Imaging ·(unknown), Cheng Chen, Meirui Jiang, Quande Liu, Jianfeng Cao, Pheng‐Ann Heng, Qi Dou	15
4	Single-Domain Generalization in Medical Image Segmentation via Test-Time Adaptation from Shape Dictionary 2022 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Quande Liu, Cheng Chen, Qi Dou, Pheng‐Ann Heng	21
5	Impact of blood pressure changes on myocardial work indices in hypertensive patients in a day 2021 ·Journal of Clinical Hypertension ·(unknown), Quande Liu, (unknown), Mengmeng Li, Yu Zhang, (unknown), Mei Zhang	13
6	Learning With Privileged Multimodal Knowledge for Unimodal Segmentation 2021 ·IEEE Transactions on Medical Imaging ·Cheng Chen, Qi Dou, Yueming Jin, Quande Liu, Pheng‐Ann Heng	63
7	FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space breakdown → 2021 ·The HKU Scholars Hub (University of Hong Kong) ·Quande Liu, Cheng Chen, Jing Qin, Qi Dou, Pheng‐Ann Heng	292
8	Contrastive Cross-Site Learning With Redesigned Net for COVID-19 CT Classification 2020 ·IEEE Journal of Biomedical and Health Informatics ·(unknown), Quande Liu, Qi Dou	154
9	Unpaired Multi-Modal Segmentation via Knowledge Distillation 2020 ·IEEE Transactions on Medical Imaging ·Qi Dou, Quande Liu, Pheng‐Ann Heng, Ben Glocker	134
10	Deep Mining External Imperfect Data for Chest X-Ray Disease Screening 2020 ·IEEE Transactions on Medical Imaging ·Luyang Luo, Lequan Yu, Hao Chen, Quande Liu, Xi Wang, (unknown), Pheng‐Ann Heng	56

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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