Gemma Piella

115 papers receiving 2.7k citations

Gemma Piella's Hit Papers

A new quality metric for image fusion 2004 · 673 citations
6730+7+14Years since publication200400600

Peers

Gemma Piella
Comparison fields: 5 of 139
  • Media Technology 971
  • Health Informatics 105
  • Computer Vision and Pattern Recognition 1.1k
  • Radiology, Nuclear Medicine and Imaging 495
  • Cardiology and Cardiovascular Medicine 373
Replace Yi Guo with:
Yi Guo China
S. Kevin Zhou United States
Ismail Ben Ayed Canada
Greg Slabaugh United Kingdom
Yi Xin China
Anjan Gudigar India
Wenjia Bai United Kingdom
J. Shin United States
Jian Yang China
Jeny Rajan India
Gemma Piella relative to Yi Guo China Yi Guo's profile →
Citations per field
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Citations per year

Countries citing papers authored by Gemma Piella

Since Specialization
Citations

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

Fields of papers citing papers by Gemma Piella

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 123 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A new quality metric for image fusion
Hit paper breakdown →
2004673
2 2018163
3 2009108
4 201893
5 201190
6 200280
7 202276
8 201870
9 200768
10 200366
11 201961
12 202060
13 202254
14 201342
15 201141
16 200236
17 200336
18 201635
19 201933
20
Adaptive wavelets and their applications to image fusion and compression
200330

About Gemma Piella

Gemma Piella is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine, Pediatrics, Perinatology and Child Health and Media Technology, having authored 123 papers that have together received 2.8k indexed citations. Recurring topics across this work include Fetal and Pediatric Neurological Disorders (24 papers), Image and Signal Denoising Methods (22 papers), Advanced Data Compression Techniques (17 papers), Advanced Image Fusion Techniques (16 papers), Cardiovascular Function and Risk Factors (15 papers), Advanced MRI Techniques and Applications (13 papers), Medical Image Segmentation Techniques (12 papers) and Neonatal and fetal brain pathology (8 papers). The work is most often cited by research in Media Technology (971 citations), Health Informatics (105 citations), Computer Vision and Pattern Recognition (1.1k citations), Radiology, Nuclear Medicine and Imaging (495 citations) and Cardiology and Cardiovascular Medicine (373 citations). Gemma Piella has collaborated with scholars based in Spain, France and United States. Frequent co-authors include H.J.A.M. Heijmans, Miguel Á. González Ballester, Nicolás Duchateau, Bart Bijnens, Mario Ceresa, E. Eixarch, Mathieu De Craene, Sergio Sanchez‐Martinez, Alejandro F. Frangi and E. Gratacós. Their work appears in journals such as Medical Image Analysis, Computer Methods and Programs in Biomedicine, IEEE Transactions on Medical Imaging, Computerized Medical Imaging and Graphics and Frontiers in Bioengineering and Biotechnology.

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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