Khai Sing Chin

402 total citations
6 papers, 284 citations indexed

About

Khai Sing Chin is a scholar working on Radiology, Nuclear Medicine and Imaging, Ophthalmology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Khai Sing Chin has authored 6 papers receiving a total of 284 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Radiology, Nuclear Medicine and Imaging, 5 papers in Ophthalmology and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Khai Sing Chin's work include Retinal Imaging and Analysis (5 papers), Glaucoma and retinal disorders (4 papers) and Retinal Diseases and Treatments (2 papers). Khai Sing Chin is often cited by papers focused on Retinal Imaging and Analysis (5 papers), Glaucoma and retinal disorders (4 papers) and Retinal Diseases and Treatments (2 papers). Khai Sing Chin collaborates with scholars based in United Kingdom, Singapore and French Polynesia. Khai Sing Chin's co-authors include Tin Aung, Nicholas G. Strouthidis, Jean Martial Mari, Michaël J. A. Girard, Emanuele Trucco, Shamira Perera, Tin A. Tun, Liang Zhang, Alexandre H. Thiéry and Peter J. Wilson and has published in prestigious journals such as Ophthalmology, Investigative Ophthalmology & Visual Science and Pattern Recognition Letters.

In The Last Decade

Khai Sing Chin

6 papers receiving 277 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Khai Sing Chin United Kingdom	5	226	199	83	61	33	6	284
Gilberto Zamora United States	11	254 1.1×	204 1.0×	132 1.6×	54 0.9×	7 0.2×	34	360
Ariel J. Tyring United States	4	262 1.2×	221 1.1×	45 0.5×	81 1.3×	5 0.2×	7	306
Hanpei Miao China	9	164 0.7×	124 0.6×	42 0.5×	29 0.5×	20 0.6×	21	253
Sajib Saha Australia	12	434 1.9×	287 1.4×	161 1.9×	91 1.5×	9 0.3×	58	603
Tsutomu Kikawa Japan	10	355 1.6×	361 1.8×	72 0.9×	37 0.6×	18 0.5×	27	424
Bettina Selig Germany	7	269 1.2×	299 1.5×	17 0.2×	28 0.5×	14 0.4×	14	358
Zoran Vatavuk Croatia	11	224 1.0×	282 1.4×	36 0.4×	26 0.4×	37 1.1×	45	375
Naofumi Ishitobi Japan	10	394 1.7×	350 1.8×	48 0.6×	41 0.7×	4 0.1×	13	470
Anita Manassakorn Thailand	11	280 1.2×	323 1.6×	27 0.3×	50 0.8×	18 0.5×	34	377
Sonja Karst Austria	14	320 1.4×	310 1.6×	46 0.6×	41 0.7×	3 0.1×	24	430

Countries citing papers authored by Khai Sing Chin

Since Specialization

Citations

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

Fields of papers citing papers by Khai Sing Chin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Khai Sing Chin. 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 Khai Sing Chin. The network helps show where Khai Sing Chin may publish in the future.

Co-authorship network of co-authors of Khai Sing Chin

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

All Works

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6 of 6 papers shown

1.

Girard, Michaël J. A., Khai Sing Chin, Tin Aung, et al.. (2018). Deep Learning can Exploit 3D Structural Information of the Optic Nerve Head to Provide a Glaucoma Diagnostic Power Superior to that of Retinal Nerve Fibre Layer Thickness. Investigative Ophthalmology & Visual Science. 59(9). 4081–4081. 2 indexed citations

2.

Zhang, Liang, Shamira Perera, Jean Martial Mari, et al.. (2018). DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images. Biomedical Optics Express. 9(7). 3244–3244. 143 indexed citations

3.

Girard, Michaël J. A., Khai Sing Chin, Eleni Nikita, et al.. (2016). In Vivo 3-Dimensional Strain Mapping of the Optic Nerve Head Following Intraocular Pressure Lowering by Trabeculectomy. Ophthalmology. 123(6). 1190–1200. 72 indexed citations

4.

Chin, Khai Sing, et al.. (2013). Automatic fovea location in retinal images using anatomical priors and vessel density. Pattern Recognition Letters. 34(10). 1152–1158. 27 indexed citations

5.

Giachetti, Andrea, et al.. (2012). Effective features for artery-vein classification in digital fundus images. Discovery Research Portal (University of Dundee). 1–6. 24 indexed citations

6.

Giachetti, Andrea, Khai Sing Chin, Emanuele Trucco, Caroline Cobb, & Peter J. Wilson. (2011). Multiresolution localization and segmentation of the optical disc in fundus images using inpainted background and vessel information. Discovery Research Portal (University of Dundee). 6512. 2145–2148. 16 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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