Matthew Brown

1.2k total citations · 1 hit paper
14 papers, 1.0k citations indexed

About

Matthew Brown is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Matthew Brown has authored 14 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Radiology, Nuclear Medicine and Imaging, 6 papers in Pulmonary and Respiratory Medicine and 2 papers in Surgery. Recurrent topics in Matthew Brown's work include Radiomics and Machine Learning in Medical Imaging (7 papers), Lung Cancer Diagnosis and Treatment (5 papers) and Cholesterol and Lipid Metabolism (2 papers). Matthew Brown is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (7 papers), Lung Cancer Diagnosis and Treatment (5 papers) and Cholesterol and Lipid Metabolism (2 papers). Matthew Brown collaborates with scholars based in United States, Canada and Netherlands. Matthew Brown's co-authors include Robert E. Hammer, Jay D. Horton, Hitoshi Shimano, Iichiro Shimomura, J L Goldstein, Jinlin Yang, Xiaodong Wang, Joseph L. Goldstein, Juro Sakai and Derek Besner and has published in prestigious journals such as Journal of Clinical Investigation, The EMBO Journal and Medical Physics.

In The Last Decade

Matthew Brown

14 papers receiving 1.0k citations

Hit Papers

Activation of cholesterol synthesis in preference to fatt... 1998 2026 2007 2016 1998 100 200 300 400 500

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Matthew Brown United States 9 550 464 158 147 131 14 1.0k
Lien B. Nguyen United States 15 353 0.6× 476 1.0× 62 0.4× 237 1.6× 92 0.7× 26 813
Alejandra Gutierrez United States 8 419 0.8× 272 0.6× 88 0.6× 120 0.8× 132 1.0× 12 749
Sampathkumar Rangasamy United States 20 611 1.1× 210 0.5× 94 0.6× 75 0.5× 173 1.3× 44 1.9k
Jenni Huusko Finland 16 578 1.1× 135 0.3× 194 1.2× 122 0.8× 91 0.7× 33 1.0k
Samira Daniel United States 14 873 1.6× 522 1.1× 108 0.7× 68 0.5× 89 0.7× 16 1.4k
Amir Gamliel United States 10 1.2k 2.1× 146 0.3× 214 1.4× 136 0.9× 196 1.5× 17 1.5k
Yalda Jamshidi United Kingdom 20 647 1.2× 111 0.2× 95 0.6× 86 0.6× 113 0.9× 38 1.3k
Kang Zhao China 10 511 0.9× 127 0.3× 91 0.6× 52 0.4× 57 0.4× 29 1.1k
Myron E. Hinsdale United States 14 535 1.0× 175 0.4× 141 0.9× 49 0.3× 69 0.5× 28 949
Martina Lukasova Germany 10 617 1.1× 182 0.4× 79 0.5× 75 0.5× 119 0.9× 13 1.2k

Countries citing papers authored by Matthew Brown

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Brown

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

All Works

14 of 14 papers shown
1.
Kockelkorn, Thessa T. J. P., Cornelia Schaefer‐Prokop, Gracijela Božović, et al.. (2014). Interactive lung segmentation in abnormal human and animal chest CT scans. Medical Physics. 41(8Part1). 81915–81915. 6 indexed citations
2.
Lo, Pechin, et al.. (2014). Bone Tumor Segmentation on Bone Scans Using Context Information and Random Forests. Lecture notes in computer science. 17(Pt 1). 601–608. 8 indexed citations
3.
Herdman, Chris M., et al.. (2014). Effects of Conversation on Situation Awareness and Working Memory in Simulated Driving. Human Factors The Journal of the Human Factors and Ergonomics Society. 56(6). 1077–1092. 46 indexed citations
4.
Rikxoort, Eva M. van, Jonathan Goldin, Maya Galperin-Aizenberg, & Matthew Brown. (2011). Classification of pulmonary emphysema from chest CT scans using integral geometry descriptors. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7963. 79631O–79631O. 1 indexed citations
5.
Brown, Matthew, Michael F. McNitt‐Gray, Richard Pais, et al.. (2007). CAD in clinical trials: Current role and architectural requirements. Computerized Medical Imaging and Graphics. 31(4-5). 332–337. 12 indexed citations
6.
Ochs, Robert, Han Jo Kim, Erin Angel, et al.. (2007). Forming a reference standard from LIDC data: impact of reader agreement on reported CAD performance. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6514. 65142A–65142A. 12 indexed citations
7.
Hou, Ming, et al.. (2007). Intelligent Adaptive Interfaces for the Control of Multiple UAVs. Journal of Cognitive Engineering and Decision Making. 1(3). 327–362. 26 indexed citations
8.
Ochs, Robert, Jonathan Goldin, Fereidoun Abtin, et al.. (2007). Multiscale shape features for classification of bronchovascular anatomy in CT using AdaBoost. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6512. 65120T–65120T. 1 indexed citations
9.
Wang, Yang, Michael F. McNitt‐Gray, Sumit K. Shah, et al.. (2007). Computer-aided characterization of solitary pulmonary nodules (SPNs) using structural 3D, texture, and functional dynamic contrast features. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6514. 651413–651413. 1 indexed citations
10.
Brown, Matthew, Jennifer A. Stolz, & Derek Besner. (2006). Dissociative effects of stimulus quality on semantic and morphological contexts in visual word recognition.. Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale. 60(3). 190–199. 15 indexed citations
11.
Shah, Sumit K., Michael F. McNitt‐Gray, Sarah R. Rogers, et al.. (2004). Computer-aided lung nodule diagnosis using a simple classifier. International Congress Series. 1268. 952–955. 4 indexed citations
12.
Brown, Matthew & Derek Besner. (2002). Semantic priming: On the role of awareness in visual word recognition in the absence of an expectancy. Consciousness and Cognition. 11(3). 402–422. 24 indexed citations
13.
Horton, Jay D., Iichiro Shimomura, Matthew Brown, et al.. (1998). Activation of cholesterol synthesis in preference to fatty acid synthesis in liver and adipose tissue of transgenic mice overproducing sterol regulatory element-binding protein-2.. Journal of Clinical Investigation. 101(11). 2331–2339. 596 indexed citations breakdown →
14.
Wang, Xiaodong, et al.. (1996). Cleavage of sterol regulatory element binding proteins (SREBPs) by CPP32 during apoptosis.. The EMBO Journal. 15(5). 1012–1020. 284 indexed citations

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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