P.E. Undrill

969 citations
35 papers · 697 · h-index 14

Impact in

Papers in

P.E. Undrill

35 papers receiving 633 citations

Peers

P.E. Undrill
Comparison fields: 5 of 96
  • Ophthalmology 153
  • Radiology, Nuclear Medicine and Imaging 329
  • Orthopedics and Sports Medicine 113
  • Computer Vision and Pattern Recognition 247
  • Artificial Intelligence 117
Replace Md Tauhidul Islam with:
Md Tauhidul Islam United States
Germán González United States
Dewey Odhner United States
Adrián Colomer Spain
Stephen Chang Singapore
Avan Suinesiaputra New Zealand
Luc Duong Canada
Zekun Jiang China
Shuqian Luo China
Ryoungwoo Jang South Korea
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Citations per year

Countries citing papers authored by P.E. Undrill

Since Specialization
Citations

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

Fields of papers citing papers by P.E. Undrill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P.E. Undrill. 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 P.E. Undrill. The network helps show where P.E. Undrill may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998162
2 199577
3 200477
4 199863
5 197343
6 199935
7 200429
8 200529
9 200023
10 199623
11 199716
12
Cranial scintigraphy: value of adding emission computed tomographic sections to conventional pertechnetate images (512 cases).
197916
13 199815
14 200013
15 199712
16 199710
17 19869
18 19886
19 19965
20 19965

About P.E. Undrill

P.E. Undrill is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering and Orthopedics and Sports Medicine, having authored 35 papers that have together received 697 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (12 papers), Medical Imaging Techniques and Applications (7 papers), Image Retrieval and Classification Techniques (6 papers), AI in cancer detection (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Bone health and osteoporosis research (4 papers), Medical Imaging and Analysis (3 papers) and Radiation Dose and Imaging (3 papers). The work is most often cited by research in Ophthalmology (153 citations), Radiology, Nuclear Medicine and Imaging (329 citations), Orthopedics and Sports Medicine (113 citations), Computer Vision and Pattern Recognition (247 citations) and Artificial Intelligence (117 citations). P.E. Undrill has collaborated with scholars based in United Kingdom, United States and Belgium. Frequent co-authors include G. Gordon Cameron, J.S. Gregory, Michael J. Cree, Peter F. Sharp, R.M. Aspden, Konstantinos K. Delibasis, John A. Olson, John V. Forrester, K C McHardy and Thomas W. Redpath. Their work appears in journals such as Physics in Medicine and Biology, British Journal of Radiology, Investigative Radiology, Clinical Radiology and Computer Methods and Programs in Biomedicine.

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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