Joanna Simpson

36 papers receiving 2.8k citations

Hit Papers

Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation 2016 · 2.1k citations
2.1k201620262019202250010001.5k2.0k

Peers

Joanna Simpson
Comparison fields: 5 of 169
  • Neurology 845
  • Computer Vision and Pattern Recognition 1.1k
  • Radiology, Nuclear Medicine and Imaging 851
  • Health Informatics 49
  • Process Chemistry and Technology 50
Replace Qianjin Feng with:
Qianjin Feng China
Andrew D. Kane United Kingdom
Sabina Tangaro Italy
Elsa D. Angelini France
Mei Chen China
Marleen de Bruijne Denmark
Enzo Ferrante Argentina
Lei Xiang China
Jinshan Tang United States
Xin Yang China
Joanna Simpson relative to Qianjin Feng China Qianjin Feng's profile →
Citations per field
00.5×1.5×2.5×
Qianjin Feng · 1×
Citations per year

Countries citing papers authored by Joanna Simpson

Since Specialization
Citations

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

Fields of papers citing papers by Joanna Simpson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
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Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
Hit paper breakdown →
20162140
15 201663
16 201234
17 2008101
18 200525
19 200343
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Infrared emission from the atmosphere above 200 km
19761

About Joanna Simpson

Joanna Simpson is a scholar working on Medical Laboratory Technology, Behavioral Neuroscience, Critical Care and Intensive Care Medicine, Endocrinology, Diabetes and Metabolism and Pharmacology, having authored 43 papers that have together received 2.9k indexed citations. Recurring topics across this work include Indoor Air Quality and Microbial Exposure (4 papers), Mycotoxins in Agriculture and Food (4 papers), Atmospheric Ozone and Climate (3 papers), Microbial Natural Products and Biosynthesis (2 papers), Pharmacogenetics and Drug Metabolism (2 papers), Diet and metabolism studies (2 papers), Mass Spectrometry Techniques and Applications (2 papers) and Spectroscopy and Laser Applications (2 papers). The work is most often cited by research in Neurology (845 citations), Computer Vision and Pattern Recognition (1.1k citations), Radiology, Nuclear Medicine and Imaging (851 citations), Health Informatics (49 citations) and Process Chemistry and Technology (50 citations). Joanna Simpson has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include David Menon, Christian Ledig, Daniel Rueckert, Virginia Newcombe, Andrew D. Kane, Ben Glocker, Konstantinos Kamnitsas, W. G. Sorenson, B. B. JARVIS and V A Robinson. Their work appears in journals such as Applied and Environmental Microbiology, Nature Communications, Cell Reports, Rapid Communications in Mass Spectrometry and The Astrophysical Journal.

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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