J.C. Klein

31 papers receiving 2.4k citations

Hit Papers

TeleOphta: Machine learning and image processing methods for teleophthalmology 2013 · 343 citations
3432001202620092017200400600

Peers

J.C. Klein
Comparison fields: 5 of 118
  • Ophthalmology 1.4k
  • Radiology, Nuclear Medicine and Imaging 1.8k
  • Computer Vision and Pattern Recognition 1.2k
  • Bioengineering 176
  • Health Information Management 135
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Citations per year

Countries citing papers authored by J.C. Klein

Since Specialization
Citations

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

Fields of papers citing papers by J.C. Klein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by J.C. Klein. 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 J.C. Klein. The network helps show where J.C. Klein may publish in the future.

Co-authors

The 25 scholars most cited alongside J.C. Klein, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with J.C. Klein Line = papers co-authored together J.C. Klein links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina
Hit paper breakdown →
2002624
2
Segmentation of vessel-like patterns using mathematical morphology and curvature evaluation
Hit paper breakdown →
2001621
3
TeleOphta: Machine learning and image processing methods for teleophthalmology
Hit paper breakdown →
2013343
4 1999234
5 2000143
6 199380
7 200267
8 201067
9 199267
10 200250
11 197248
12 199443
13 200234
14 199730
15 198230
16 200622
17
A region merging algorithm using mathematical morphology: application to macula detection
199821
18 200720
19 199814
20 199311

About J.C. Klein

J.C. Klein is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, Ophthalmology and Molecular Biology, having authored 31 papers that have together received 2.6k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (8 papers), Electrochemical sensors and biosensors (6 papers), Medical Image Segmentation Techniques (5 papers), Diabetes Management and Research (4 papers), Retinal Diseases and Treatments (4 papers), Pancreatic function and diabetes (3 papers), Analytical Chemistry and Sensors (3 papers) and Cancer Research and Treatments (2 papers). The work is most often cited by research in Ophthalmology (1.4k citations), Radiology, Nuclear Medicine and Imaging (1.8k citations), Computer Vision and Pattern Recognition (1.2k citations), Bioengineering (176 citations) and Health Information Management (135 citations). J.C. Klein has collaborated with scholars based in France, United States and Germany. Frequent co-authors include F. Zana, Ali Erginay, Pascale Massin, Thomas Walter, George S. Wilson, G. Reach, Raeann Gifford, François Lemonnier, Vincent Poitout and D. Moatti-Sirat. Their work appears in journals such as Diabetologia, Biosensors and Bioelectronics, JNCI Journal of the National Cancer Institute, IEEE Transactions on Medical Imaging and Diabetes & Metabolism.

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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