Fiona Fennessy

10.0k citations
9 papers · 6.5k indexed · 2 hit papers · h-index 8
Topics
Radiomics and Machine Learning in Medical Imaging (3 papers)MRI in cancer diagnosis (3 papers)Tuberous Sclerosis Complex Research (1 paper)

In The Last Decade

Fiona Fennessy

9 papers receiving 6.4k citations

Hit Papers

3D Slicer as an image computing platform for the Quantita...20122026201620212012201710002.0k3.0k4.0k5.0k

Peers

Fiona Fennessy
Comparison fields: 5 of 176
  • Radiology, Nuclear Medicine and Imaging 2.7k
  • Biomedical Engineering 1.5k
  • Pulmonary and Respiratory Medicine 1.3k
  • Surgery 1.2k
  • Epidemiology 487
Replace Sonia Pujol with:
Sonia Pujol United States
Reinhard Beichel United States
Julien Finet France
James V. Miller United States
Dominique Jennings United States
Stephen Aylward United States
Heather C. Hazlett United States
Rachel G. Smith United States
Sean Ho United States
Jean‐Christophe Fillion‐Robin United States
Fiona Fennessy relative to Sonia Pujol United States Sonia Pujol's profile →
Citations per field
00.5×1.5×
Sonia Pujol · 1×
Citations per year

Countries citing papers authored by Fiona Fennessy

Since Specialization
Citations

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

Fields of papers citing papers by Fiona Fennessy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fiona Fennessy

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

All Works

9 of 9 papers shown
#WorkIndexed citations
1 26
2
Somatic Mutations Drive Distinct Imaging Phenotypes in Lung Cancerbreakdown →
304
3 23
4
3D Slicer as an image computing platform for the Quantitative Imaging Networkbreakdown →
5750
5 159
6 2
7 42
8 12
9 183

About Fiona Fennessy

Fiona Fennessy is a scholar working on Radiology, Nuclear Medicine and Imaging, Clinical Biochemistry and Obstetrics and Gynecology, having authored 9 papers that have together received 6.5k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (3 papers), MRI in cancer diagnosis (3 papers) and Tuberous Sclerosis Complex Research (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (2.7k citations), Health Informatics (83 citations) and Oral Surgery (336 citations). Fiona Fennessy has collaborated with scholars based in United States, Germany and Ireland. Frequent co-authors include Andriy Fedorov, Ron Kikinis, Steve Pieper, Sonia Pujol, Jean‐Christophe Fillion‐Robin, Christian Bauer, Dominique Jennings, Milan Sonka, James V. Miller and Jayashree Kalpathy–Cramer. Their work appears in journals such as PLoS ONE, Cancer Research and American Journal of Physiology-Cell Physiology.

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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