Dakai Jin

2.5k total citations · 1 hit paper
35 papers, 697 citations indexed

About

Dakai Jin is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Dakai Jin has authored 35 papers receiving a total of 697 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Radiology, Nuclear Medicine and Imaging, 14 papers in Computer Vision and Pattern Recognition and 12 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Dakai Jin's work include Radiomics and Machine Learning in Medical Imaging (12 papers), Medical Imaging Techniques and Applications (12 papers) and Medical Image Segmentation Techniques (9 papers). Dakai Jin is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (12 papers), Medical Imaging Techniques and Applications (12 papers) and Medical Image Segmentation Techniques (9 papers). Dakai Jin collaborates with scholars based in United States, China and Cayman Islands. Dakai Jin's co-authors include Punam K. Saha, Le Lü, Dazhou Guo, Eric A. Hoffman, Cheng Chen, Jing Xiao, Krishna Iyer, Adam P. Harrison, Puyang Wang and Zihan Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, American Journal of Respiratory and Critical Care Medicine and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

Dakai Jin

33 papers receiving 691 citations

Hit Papers

LViT: Language Meets Vision Transformer in Medical Image ... 2023 2026 2024 2025 2023 40 80 120
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. LViT: Language Meets Vision Transformer in Medical Image Segmentation
    2023 135 citations Zihan Li, Yunxiang Li et al. IEEE Transactions on Medical Imaging profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dakai Jin United States 15 370 208 154 149 138 35 697
Xiangrong Zhou Japan 12 363 1.0× 263 1.3× 164 1.1× 268 1.8× 59 0.4× 42 838
Hanns‐Christian Breit Switzerland 11 541 1.5× 82 0.4× 93 0.6× 278 1.9× 133 1.0× 41 797
Nathan Lay United States 18 747 2.0× 302 1.5× 262 1.7× 251 1.7× 633 4.6× 50 1.2k
Kyong Joon Lee South Korea 14 217 0.6× 75 0.4× 80 0.5× 88 0.6× 97 0.7× 40 575
Brent Foster United States 13 671 1.8× 265 1.3× 125 0.8× 169 1.1× 272 2.0× 30 1.0k
Tomas Sakinis Norway 7 265 0.7× 68 0.3× 103 0.7× 92 0.6× 52 0.4× 10 499
Soichiro Miki Japan 14 323 0.9× 71 0.3× 152 1.0× 94 0.6× 203 1.5× 51 659
Ryan Amelon United States 7 754 2.0× 210 1.0× 90 0.6× 68 0.5× 64 0.5× 15 945
Joshy Cyriac Switzerland 11 496 1.3× 83 0.4× 95 0.6× 271 1.8× 131 0.9× 22 789

Countries citing papers authored by Dakai Jin

Since Specialization
Citations

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

Fields of papers citing papers by Dakai Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dakai Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Dakai Jin. A scholar is included among the top collaborators of Dakai Jin 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 Dakai Jin. Dakai Jin 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
1.
Wei, Ran, Dakai Jin, Xianghua Ye, et al.. (2025). DistAL: A Domain-Shift Active Learning Framework With Transferable Feature Learning for Lesion Detection. IEEE Transactions on Medical Imaging. 44(7). 3038–3050.
2.
Xia, Yingda, Zhihong Chen, Suyun Li, et al.. (2024). A Colorectal Coordinate-Driven Method for Colorectum and Colorectal Cancer Segmentation in Conventional CT Scans. IEEE Transactions on Neural Networks and Learning Systems. 36(4). 7395–7406. 4 indexed citations
3.
Mok, Tony C. W., Yunhao Bai, Jianpeng Zhang, et al.. (2024). Modality-Agnostic Structural Image Representation Learning for Deformable Multi-Modality Medical Image Registration. 11215–11225. 5 indexed citations
4.
Wang, Puyang, Dazhou Guo, Dandan Zheng, et al.. (2024). Accurate Airway Tree Segmentation in CT Scans via Anatomy-Aware Multi-Class Segmentation and Topology-Guided Iterative Learning. IEEE Transactions on Medical Imaging. 43(12). 4294–4306. 6 indexed citations
5.
Wang, Pei, Jia Ge, Dandan Zheng, et al.. (2023). Anatomy-Guided Deep Learning Model for Accurate and Robust Gross Tumor Volume Segmentation in Lung Cancer Radiation Therapy. International Journal of Radiation Oncology*Biology*Physics. 117(2). e71–e71. 1 indexed citations
6.
Zhang, Yongfeng, Xiangyang Ye, Junbo Ge, et al.. (2023). Deep Learning-Based Multi-Modality Segmentation of Primary Gross Tumor Volume in CT and MRI for Nasopharyngeal Carcinoma. International Journal of Radiation Oncology*Biology*Physics. 117(2). e498–e498. 3 indexed citations
7.
8.
Li, Zihan, Yunxiang Li, Qingde Li, et al.. (2023). LViT: Language Meets Vision Transformer in Medical Image Segmentation. IEEE Transactions on Medical Imaging. 43(1). 96–107. 135 indexed citations breakdown →
9.
Jin, Dakai, Dazhou Guo, Jia Ge, Xianghua Ye, & Le Lü. (2022). Towards automated organs at risk and target volumes contouring: Defining precision radiation therapy in the modern era. SHILAP Revista de lepidopterología. 2(4). 306–313. 9 indexed citations
10.
Nikpanah, Moozhan, Ziyue Xu, Dakai Jin, et al.. (2021). A deep-learning based artificial intelligence (AI) approach for differentiation of clear cell renal cell carcinoma from oncocytoma on multi-phasic MRI. Clinical Imaging. 77. 291–298. 31 indexed citations
11.
Guo, Dazhou, Jia Ge, Xing Di, et al.. (2021). Anatomy Guided Thoracic Lymph Node Station Delineation in CT Using Deep Learning Model. International Journal of Radiation Oncology*Biology*Physics. 111(3). e120–e121. 2 indexed citations
12.
Guo, Dazhou, Dakai Jin, Zhuotun Zhu, et al.. (2020). Organ at Risk Segmentation for Head and Neck Cancer Using Stratified Learning and Neural Architecture Search. 4222–4231. 33 indexed citations
13.
Li, Zhang, Zhong Zheng, Tianyu Zhang, et al.. (2020). From community-acquired pneumonia to COVID-19: a deep learning–based method for quantitative analysis of COVID-19 on thick-section CT scans. European Radiology. 30(12). 6828–6837. 62 indexed citations
14.
Jin, Dakai, Dazhou Guo, Tsung‐Ying Ho, et al.. (2020). DeepTarget: Gross tumor and clinical target volume segmentation in esophageal cancer radiotherapy. Medical Image Analysis. 68. 101909–101909. 46 indexed citations
15.
Saha, Punam K., et al.. (2017). Fuzzy Object Skeletonization: Theory, Algorithms, and Applications. IEEE Transactions on Visualization and Computer Graphics. 24(8). 2298–2314. 20 indexed citations
16.
17.
Jin, Dakai, et al.. (2016). A semi-automatic framework of measuring pulmonary arterial metrics at anatomic airway locations using CT imaging. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9788. 978816–978816. 5 indexed citations
18.
Iyer, Krishna, John D. Newell, Dakai Jin, et al.. (2015). Quantitative Dual-Energy Computed Tomography Supports a Vascular Etiology of Smoking-induced Inflammatory Lung Disease. American Journal of Respiratory and Critical Care Medicine. 193(6). 652–661. 69 indexed citations
19.
Li, Cheng, Dakai Jin, Cheng Chen, et al.. (2015). Automated cortical bone segmentation for multirow‐detector CT imaging with validation and application to human studies. Medical Physics. 42(8). 4553–4565. 19 indexed citations
20.
Jin, Dakai, Krishna Iyer, Eric A. Hoffman, & Punam K. Saha. (2014). A New Approach of Arc Skeletonization for Tree-like Objects Using Minimum Cost Path. PubMed. 2014. 942–947. 4 indexed citations

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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