Chu Han

2.4k citations
69 papers · 1.4k · 2 hit papers · h-index 21

Impact in

Papers in

Chu Han

62 papers receiving 1.4k citations

Chu Han's Hit Papers

MRI-based Quantification of Intratumoral Heterogeneity for Predicting Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer 2023 · 112 citations
1120+1+2Years since publication255075100

Peers

Chu Han
Comparison fields: 5 of 127
  • Computer Vision and Pattern Recognition 637
  • Computational Mathematics 15
  • Radiology, Nuclear Medicine and Imaging 543
  • Artificial Intelligence 563
  • Neurology 133
Replace Idit Diamant with:
Idit Diamant Israel
Yinghuan Shi China
Xiaoshuang Shi China
Zhenbing Liu China
Mislav Grgić Croatia
Maximilian Baust Germany
Xinyu Liu China
Lei He China
Chu Han relative to Idit Diamant Israel Idit Diamant's profile →
Citations per field
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Idit Diamant · 1×
Citations per year

Countries citing papers authored by Chu Han

Since Specialization
Citations

This map shows the geographic impact of Chu Han'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 Chu Han with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chu Han more than expected).

Fields of papers citing papers by Chu Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chu Han. 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 Chu Han. The network helps show where Chu Han may publish in the future.

Co-authors

The 25 scholars most cited alongside Chu Han, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chu Han Line = papers co-authored together Chu Han links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1
MRI-based Quantification of Intratumoral Heterogeneity for Predicting Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer
Hit paper breakdown →
2023112
2
CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer With Modality-Correlated Cross-Attention for Brain Tumor Segmentation
Hit paper breakdown →
2023103
3 2020102
4 201780
5 202179
6 202372
7 202268
8 202356
9 201853
10 202141
11 202239
12 202038
13 202337
14 201936
15 202233
16 201832
17 202230
18 202227
19 202124
20 202323

About Chu Han

Chu Han is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Oncology and Biomedical Engineering, having authored 69 papers that have together received 1.4k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (32 papers), AI in cancer detection (27 papers), Digital Imaging for Blood Diseases (10 papers), Advanced Image and Video Retrieval Techniques (7 papers), Image Enhancement Techniques (6 papers), Advanced Neural Network Applications (5 papers), Colorectal Cancer Surgical Treatments (5 papers) and Advanced Vision and Imaging (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (637 citations), Computational Mathematics (15 citations), Radiology, Nuclear Medicine and Imaging (543 citations), Artificial Intelligence (563 citations) and Neurology (133 citations). Chu Han has collaborated with scholars based in China, Hong Kong and Netherlands. Frequent co-authors include Zaiyi Liu, Guoqiang Han, Xipeng Pan, Zhenwei Shi, Zeyan Xu, Jing Qin, Shengfeng He, Changhong Liang, Bingchao Zhao and Huan Lin. Their work appears in journals such as Medical Image Analysis, Neurocomputing, IEEE Transactions on Medical Imaging, IEEE Transactions on Neural Networks and Learning Systems and Expert Systems with Applications.

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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