Derek Magee

3.1k citations
95 papers · 2.1k indexed · 1 hit paper · h-index 24

Impact in

Papers in

Derek Magee

91 papers receiving 2.0k citations

Hit Papers

A Nonlinear Mapping Approach to Stain Normalization in Digital Histopathology Images Using Image-Specific Color Deconvolution 2014 · 384 citations
3842014202620182022100200300

Peers

Derek Magee
Comparison fields: 5 of 147
  • Biophysics 273
  • Computer Vision and Pattern Recognition 767
  • Artificial Intelligence 739
  • Radiology, Nuclear Medicine and Imaging 495
  • Ocean Engineering 237
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Citations per year

Countries citing papers authored by Derek Magee

Since Specialization
Citations

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

Fields of papers citing papers by Derek Magee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 95 papers — load more, or switch the sort, to bring in the rest.

#Work
1
A Nonlinear Mapping Approach to Stain Normalization in Digital Histopathology Images Using Image-Specific Color Deconvolution
Hit paper breakdown →
2014384
2 2016174
3 2003157
4 2012114
5
Colour Normalisation in Digital Histopathology Images
200985
6 201868
7 200767
8 201360
9 202056
10 201453
11 200238
12 201534
13 201533
14 200933
15 201932
16
Modeling interaction using learnt qualitative spatio-temporal relations and variable length Markov Models
200229
17 200529
18 201429
19 201829
20 200928

About Derek Magee

Derek Magee is a scholar working on Computer Vision and Pattern Recognition, Biophysics, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Oncology, having authored 95 papers that have together received 2.1k indexed citations. Recurring topics across this work include AI in cancer detection (24 papers), Medical Image Segmentation Techniques (14 papers), Advanced MRI Techniques and Applications (11 papers), Radiomics and Machine Learning in Medical Imaging (10 papers), Cell Image Analysis Techniques (9 papers), Cardiac Imaging and Diagnostics (9 papers), Colorectal Cancer Surgical Treatments (9 papers) and Medical Imaging Techniques and Applications (8 papers). The work is most often cited by research in Biophysics (273 citations), Computer Vision and Pattern Recognition (767 citations), Artificial Intelligence (739 citations), Radiology, Nuclear Medicine and Imaging (495 citations) and Ocean Engineering (237 citations). Derek Magee has collaborated with scholars based in United Kingdom, Netherlands and Sweden. Frequent co-authors include Darren Treanor, Nasir Rajpoot, Adnan Mujahid Khan, Anthony G. Cohn, Lijun Wei, Philip Quirke, Andrew J. Bulpitt, Yi Song, Nicholas Roberts and D. Crellin. Their work appears in journals such as Journal of Pathology Informatics, Physics in Medicine and Biology, Histopathology, Journal of Cardiovascular Magnetic Resonance and Image and Vision Computing.

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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