Miaofei Han

1.3k citations
16 papers · 481 indexed · h-index 11
Topics
Radiomics and Machine Learning in Medical Imaging (11 papers)Medical Image Segmentation Techniques (4 papers)COVID-19 diagnosis using AI (4 papers)

In The Last Decade

Miaofei Han

16 papers receiving 474 citations

Peers

Miaofei Han
Comparison fields: 5 of 65
  • Radiology, Nuclear Medicine and Imaging 347
  • Artificial Intelligence 134
  • Pulmonary and Respiratory Medicine 103
  • Biomedical Engineering 93
  • Computer Vision and Pattern Recognition 81
Replace Bruno Oliveira with:
Bruno Oliveira Portugal
Saikit Lam Hong Kong
Fredrik Löfman Sweden
Yazdan Salimi Switzerland
Azadeh Akhavanallaf Switzerland
Siu Ki Yu Hong Kong
Johannes Hofmanninger Austria
Amirhossein Sanaat Switzerland
John A. Onofrey United States
Atallah Baydoun United States
Miaofei Han relative to Bruno Oliveira Portugal Bruno Oliveira's profile →
Citations per field
00.5×
Bruno Oliveira · 1×
Citations per year

Countries citing papers authored by Miaofei Han

Since Specialization
Citations

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

Fields of papers citing papers by Miaofei Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miaofei Han

This figure shows the co-authorship network connecting the top 25 collaborators of Miaofei Han. A scholar is included among the top collaborators of Miaofei Han 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 Miaofei Han. Miaofei Han is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
#WorkIndexed citations
1 12
2 10
3 13
4 4
5 74
6 6
7 52
8 54
9 136
10 30
11 8
12 7
13
Segmentation of CT Thoracic Organs by Multi-resolution VB-nets.
30
14 11
15
Fast filtering techniques in medical image classification and retrieval
3
16 31

About Miaofei Han

Miaofei Han is a scholar working on Radiology, Nuclear Medicine and Imaging, Radiation and General Materials Science, having authored 16 papers that have together received 481 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (11 papers), Medical Image Segmentation Techniques (4 papers) and COVID-19 diagnosis using AI (4 papers). The work is most often cited by research in Health Informatics (35 citations), Radiology, Nuclear Medicine and Imaging (347 citations) and Radiation (73 citations). Miaofei Han has collaborated with scholars based in China, South Korea and Australia. Frequent co-authors include Yaozong Gao, Dinggang Shen, Fei Shan, Zhong Xue, Weiya Shi, Jun Wang, Yuxin Shi, Nannan Shi, Guang Yao and Yiqiang Zhan. Their work appears in journals such as Nature Communications, IEEE Transactions on Medical Imaging and Medical Physics.

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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