Lin Han

2.9k citations
50 papers · 1.2k · 1 hit paper · h-index 12

Impact in

Papers in

Lin Han

42 papers receiving 1.2k citations

Hit Papers

Segment anything in medical images 2024 · 896 citations
8960+1Years since publication250500750

Peers

Lin Han
Comparison fields: 5 of 137
  • Health Informatics 55
  • Computer Vision and Pattern Recognition 426
  • Radiology, Nuclear Medicine and Imaging 380
  • Neurology 109
  • Artificial Intelligence 372
Replace Sidike Paheding with:
Sidike Paheding United States
Nahian Siddique United States
Simon Jégou France
Colin Elkin United States
Haofan Wang China
Lei Xiang China
Moein Heidari Iran
Mainak Biswas India
Parvin Mousavi Canada
Ehsan Khodapanah Aghdam Iran
Lin Han relative to Sidike Paheding United States Sidike Paheding's profile →
Citations per field
00.5×10×17×
Sidike Paheding · 1×
Citations per year

Countries citing papers authored by Lin Han

Since Specialization
Citations

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

Fields of papers citing papers by Lin Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Segment anything in medical images
Hit paper breakdown →
2024896
2 202233
3 202232
4 202030
5 202228
6 201718
7 202116
8 202314
9 202014
10 202113
11 201912
12 202311
13 20198
14 20197
15 20197
16 20227
17 20246
18 20234
19 20234
20 20194

About Lin Han

Lin Han is a scholar working on Artificial Intelligence, Global and Planetary Change, Atmospheric Science, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 50 papers that have together received 1.2k indexed citations. Recurring topics across this work include Atmospheric aerosols and clouds (10 papers), AI in cancer detection (9 papers), Thyroid Cancer Diagnosis and Treatment (7 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), Solar Radiation and Photovoltaics (6 papers), Atmospheric chemistry and aerosols (5 papers), Atmospheric Ozone and Climate (4 papers) and Thyroid and Parathyroid Surgery (3 papers). The work is most often cited by research in Health Informatics (55 citations), Computer Vision and Pattern Recognition (426 citations), Radiology, Nuclear Medicine and Imaging (380 citations), Neurology (109 citations) and Artificial Intelligence (372 citations). Lin Han has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Bo Wang, Jun Ma, Yuting He, Chenyu You, Feng Zhang, Jiangli Lin, Jun Li, Wenwen Li, Yan Zhuang and Lap–Kei Lee. Their work appears in journals such as Journal of X-Ray Science and Technology, Journal of Quantitative Spectroscopy and Radiative Transfer, IEEE Transactions on Geoscience and Remote Sensing, Sensors and Remote Sensing of Environment.

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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