Getao Du

658 citations
12 papers · 441 · 1 hit paper · h-index 8

Impact in

Papers in

Getao Du

11 papers receiving 430 citations

Hit Papers

Medical Image Segmentation based on U-Net: A Review 2020 · 345 citations
3450+2+4Years since publication100200300

Peers

Getao Du
Comparison fields: 5 of 106
  • Computer Vision and Pattern Recognition 131
  • Neurology 52
  • Radiology, Nuclear Medicine and Imaging 129
  • Health Informatics 5
  • Artificial Intelligence 88
Replace Laurent Massoptier with:
Laurent Massoptier Italy
Weihao Xie China
Zitao Zeng China
Hans Meine Germany
Xinhua Cao United States
Rudi Deklerck Belgium
Jianan Chen China
Shen Zhao China
Yinghao Zhang China
Getao Du relative to Laurent Massoptier Italy Laurent Massoptier's profile →
Citations per field
00.5×11.3×
Laurent Massoptier · 1×
Citations per year

Countries citing papers authored by Getao Du

Since Specialization
Citations

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

Fields of papers citing papers by Getao Du

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Getao Du, 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 Getao Du Line = papers co-authored together Getao Du links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1
Medical Image Segmentation based on U-Net: A Review
Hit paper breakdown →
2020345
2 202017
3 202216
4 202015
5 202213
6 202013
7 20209
8 20207
9 20243
10 20242
11 20211
12 20230

About Getao Du

Getao Du is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Biomedical Engineering, Computer Vision and Pattern Recognition and Biomaterials, having authored 12 papers that have together received 441 indexed citations. Recurring topics across this work include Digital Imaging for Blood Diseases (2 papers), Nanoplatforms for cancer theranostics (2 papers), Natural product bioactivities and synthesis (2 papers), Photodynamic Therapy Research Studies (2 papers), Sesquiterpenes and Asteraceae Studies (2 papers), Nanoparticle-Based Drug Delivery (2 papers), Diabetic Foot Ulcer Assessment and Management (2 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (131 citations), Neurology (52 citations), Radiology, Nuclear Medicine and Imaging (129 citations), Health Informatics (5 citations) and Artificial Intelligence (88 citations). Getao Du has collaborated with scholars based in China and Saint Kitts and Nevis. Frequent co-authors include Yonghua Zhan, Xueli Chen, Xu Cao, Jimin Liang, Wenhua Zhan, Yun Zeng, Yayan Wu, Xinyue Liu, Dexin Zhang and Yingying Guo. Their work appears in journals such as Biomedical Signal Processing and Control, Journal of Pharmacy and Pharmacology, Frontiers in Oncology, Journal of Digital Imaging and RSC Advances.

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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