Carmen Serrano

61 papers receiving 1.1k citations

Peers

Carmen Serrano
Comparison fields: 5 of 127
  • Occupational Therapy 126
  • Rehabilitation 179
  • Cognitive Neuroscience 188
  • Computer Vision and Pattern Recognition 194
  • Oncology 257
Replace Begoña Acha with:
Begoña Acha Spain
Karl Thurnhofer‐Hemsi Spain
Samuel Ortega Spain
Mohamed Attia Australia
Mun‐Taek Choi South Korea
Konstantinos Sirlantzis United Kingdom
Suman Tewary India
Ali Mahloojifar Iran
Zhiqin Qian China
Ewa Piętka Poland
Carmen Serrano relative to Begoña Acha Spain Begoña Acha's profile →
Citations per field
00.5×1.5×
Begoña Acha · 1×
Citations per year

Countries citing papers authored by Carmen Serrano

Since Specialization
Citations

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

Fields of papers citing papers by Carmen Serrano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Carmen Serrano, 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 Carmen Serrano Line = papers co-authored together Carmen Serrano links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2013230
2 201284
3 201462
4 200860
5 199954
6 200854
7 200549
8 201543
9 200543
10 201241
11 201338
12 201128
13 201026
14 201622
15 200921
16 201121
17 201318
18 200318
19 202216
20 200416

About Carmen Serrano

Carmen Serrano is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Oncology, Rehabilitation and Ophthalmology, having authored 62 papers that have together received 1.2k indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (10 papers), Retinal Imaging and Analysis (9 papers), Cutaneous Melanoma Detection and Management (8 papers), Wound Healing and Treatments (8 papers), Advanced Data Compression Techniques (6 papers), Retinal Diseases and Treatments (6 papers), Advanced Memory and Neural Computing (6 papers) and melanin and skin pigmentation (5 papers). The work is most often cited by research in Occupational Therapy (126 citations), Rehabilitation (179 citations), Cognitive Neuroscience (188 citations), Computer Vision and Pattern Recognition (194 citations) and Oncology (257 citations). Carmen Serrano has collaborated with scholars based in Spain, Canada and United States. Frequent co-authors include Begoña Acha, Tomás Gómez‐Cía, J. A. Pérez‐Carrasco, Laura M. Roa, Teresa Serrano‐Gotarredona, B. Linares-Barranco, Irene Fondón, Aurora Sáez, Bo Zhao and Shouchun Chen. Their work appears in journals such as Burns, Machine Vision and Applications, Journal of Biomedical Optics, International Journal of Computer Assisted Radiology and Surgery and Pattern Recognition.

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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