Xiaohong Jia

2.6k citations
39 papers · 1.8k indexed · 1 hit paper · h-index 16
Topics
Medical Image Segmentation Techniques (8 papers)AI in cancer detection (8 papers)Radiomics and Machine Learning in Medical Imaging (7 papers)
Journals
Nature CommunicationsSHILAP Revista de lepidopterologíaIEEE Access

In The Last Decade

Xiaohong Jia

35 papers receiving 1.7k citations

Hit Papers

Significantly Fast and Robust Fuzzy C-Means Clustering Al...20182026202020232018100200300

Peers

Xiaohong Jia
Comparison fields: 5 of 129
  • Computer Vision and Pattern Recognition 615
  • Media Technology 373
  • Animal Science and Zoology 352
  • Artificial Intelligence 318
  • Molecular Biology 317
Replace Tianyu Guo with:
Tianyu Guo China
Lihong Zheng Australia
Ye Yuan China
Jinshan Tang United States
Tong Yang China
Davis United States
Weichuan Yu Hong Kong
Scott E. Umbaugh United States
Mohammad Hossein Rohban Iran
Xiaohong Jia relative to Tianyu Guo China Tianyu Guo's profile →
Citations per field
00.5×4.6×
Tianyu Guo · 1×
Citations per year

Countries citing papers authored by Xiaohong Jia

Since Specialization
Citations

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

Fields of papers citing papers by Xiaohong Jia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaohong Jia

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 8
3 3
4 12
5 4
6
Clinical Application of Computer-Aided Diagnosis for Breast Ultrasonography: Factors That Lead to Discordant Results in Radial and Antiradial Planes
6
7 1
8 14
9 200
10 4
11 3
12 6
13 15
14 0
15
Adaptive Morphological Reconstruction for Seeded Image Segmentation
62
16 271
17 33
18 85
19 82
20 86

About Xiaohong Jia

Xiaohong Jia is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Instrumentation, having authored 39 papers that have together received 1.8k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (8 papers), AI in cancer detection (8 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). The work is most often cited by research in Media Technology (373 citations), Animal Science and Zoology (352 citations) and Computer Vision and Pattern Recognition (615 citations). Xiaohong Jia has collaborated with scholars based in China, United Kingdom and Norway. Frequent co-authors include Tao Lei, Asoke K. Nandi, Hongying Meng, Yanning Zhang, Kristin Hollung, Kjell Ivar Hildrum, Shigang Liu, Lifeng He, L. Aass and Ellen Mosleth Færgestad. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and IEEE Access.

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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