Gobert Lee

446 total citations
33 papers, 271 citations indexed

About

Gobert Lee is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Gobert Lee has authored 33 papers receiving a total of 271 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 18 papers in Computer Vision and Pattern Recognition and 12 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Gobert Lee's work include AI in cancer detection (21 papers), Medical Image Segmentation Techniques (11 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). Gobert Lee is often cited by papers focused on AI in cancer detection (21 papers), Medical Image Segmentation Techniques (11 papers) and Radiomics and Machine Learning in Medical Imaging (8 papers). Gobert Lee collaborates with scholars based in Australia, Japan and China. Gobert Lee's co-authors include Mariusz Bajger, Hiroshi Fujita, Takeshi Hara, Xiangrong Zhou, Martin Caon, Daisuke Fukuoka, Yoshikazu Uchiyama, Yuji Hatanaka, Yoshinori Hayashi and Xin Gao and has published in prestigious journals such as SHILAP Revista de lepidopterología, Pattern Recognition Letters and Computer Methods and Programs in Biomedicine.

In The Last Decade

Gobert Lee

30 papers receiving 259 citations

Peers

Gobert Lee
Hongchun Lu China
Vivek Natarajan United States
Yangqin Feng Singapore
Aaron Loh United States
Nils Gessert Germany
Lisa Di Jorio Canada
Ruibin Feng United States
Zhaobang Liu China
Gabriel Efrain Humpire Mamani Netherlands
Hongchun Lu China
Gobert Lee
Citations per year, relative to Gobert Lee Gobert Lee (= 1×) peers Hongchun Lu

Countries citing papers authored by Gobert Lee

Since Specialization
Citations

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

Fields of papers citing papers by Gobert Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gobert Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Gobert Lee. A scholar is included among the top collaborators of Gobert Lee 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 Gobert Lee. Gobert Lee 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.
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Wells, Adam J., Mariusz Bajger, Gobert Lee, et al.. (2023). Imaging evaluation of a proposed 3D generative model for MRI to CT translation in the lumbar spine. The Spine Journal. 23(11). 1602–1612. 11 indexed citations
3.
Lee, Gobert, et al.. (2022). Enhanced Passive Stormwater Infiltration Improves Urban Melia Azedarach Functioning in Dry Season. Frontiers in Climate. 4. 4 indexed citations
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Bajger, Mariusz, Minh‐Son To, Gobert Lee, et al.. (2021). Lumbar Spine CT synthesis from MR images using CycleGAN - a preliminary study. 1–8. 2 indexed citations
6.
Bajger, Mariusz, et al.. (2019). SRM Superpixel Merging Framework for Precise Segmentation of Cervical Nucleus. 1–8. 8 indexed citations
7.
Bajger, Mariusz, et al.. (2019). Prior Guided Segmentation and Nuclei Feature Based Abnormality Detection in Cervical Cells. 742–746. 5 indexed citations
8.
Lee, Gobert, Mariusz Bajger, & Kevin Clark. (2018). Deep learning and color variability in breast cancer histopathological images: a preliminary study. 5–5. 5 indexed citations
9.
Bajger, Mariusz, et al.. (2018). Segmentation of cervical nuclei using SLIC and pairwise regional contrast. PubMed. 2018. 3422–3425. 8 indexed citations
10.
Bajger, Mariusz, et al.. (2017). Circular shape constrained fuzzy clustering (CiscFC) for nucleus segmentation in Pap smear images. Computers in Biology and Medicine. 85. 13–23. 22 indexed citations
11.
Guo, Feng, Haifeng Shen, Youhong Tang, et al.. (2017). On the Feasibility of a Smartphone-based Solution to Rapid Quantitative Urinalysis using Nanomaterial Bioprobes. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 523–524. 1 indexed citations
12.
Bajger, Mariusz, et al.. (2015). Segmentation of Breast Masses in Local Dense Background Using Adaptive Clip Limit-CLAHE. 1–8. 8 indexed citations
13.
Caon, Martin, et al.. (2014). Computer-assisted segmentation of CT images by statistical region merging for the production of voxel models of anatomy for CT dosimetry. Australasian Physical & Engineering Sciences in Medicine. 37(2). 393–403. 6 indexed citations
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Morita, Takako, Daisuke Fukuoka, Takeshi Hara, et al.. (2009). Automated analysis of breast parenchymal patterns in whole breast ultrasound images: preliminary experience. International Journal of Computer Assisted Radiology and Surgery. 4(3). 299–306. 10 indexed citations
16.
Lee, Gobert, Masayuki Kanematsu, Hiroki Kato, et al.. (2008). K-means clustering and classification of medical images based on regions-of-interest. IEICE technical report. Speech. 107(461). 55–56. 1 indexed citations
17.
Fujita, Hiroshi, Yoshikazu Uchiyama, Toshiaki Nakagawa, et al.. (2008). Computer-aided diagnosis: The emerging of three CAD systems induced by Japanese health care needs. Computer Methods and Programs in Biomedicine. 92(3). 238–248. 71 indexed citations
18.
Zhou, Xiangrong, Takeshi Hara, Hiroshi Fujita, et al.. (2008). Automated segmentation of mammary gland regions in non-contrast X-ray CT images. Computerized Medical Imaging and Graphics. 32(8). 699–709. 10 indexed citations
19.
Zhang, Xuejun, Gobert Lee, Masayuki Kanematsu, et al.. (2007). Segmentation of liver region with tumorous tissues. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6512. 651235–651235. 9 indexed citations
20.
Lee, Gobert & Murk J. Bottema. (2003). Statistical significance of Az scores: classification of masses in screening mammograms as benign or malignant based on high dimensional texture feature space. Flinders Academic Commons (Flinders University). 1 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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