Elizabeth D. Brown

2.6k citations
16 papers · 1.8k indexed · 1 hit paper · h-index 13
Topics
MRI in cancer diagnosis (5 papers)Hepatocellular Carcinoma Treatment and Prognosis (4 papers)Pediatric Urology and Nephrology Studies (3 papers)

In The Last Decade

Elizabeth D. Brown

16 papers receiving 1.7k citations

Hit Papers

3D statistical neuroanatomical models from 305 MRI volumes200520262012201920052505007501000

Peers

Elizabeth D. Brown
Comparison fields: 5 of 105
  • Cognitive Neuroscience 663
  • Radiology, Nuclear Medicine and Imaging 618
  • Hepatology 259
  • Surgery 256
  • Pulmonary and Respiratory Medicine 209
Replace Wolfgang Burchert with:
Wolfgang Burchert Germany
Jee Eun Lee United States
H. Hundeshagen Germany
Hong Yin China
Norman C. Wang United States
Marco Aiello Italy
Hans‐Jörg Wittsack Germany
Vincent Noblet France
Ahmed Soliman United States
Yong An Chung South Korea
Elizabeth D. Brown relative to Wolfgang Burchert Germany Wolfgang Burchert's profile →
Citations per field
00.5×1.5×
Wolfgang Burchert · 1×
Citations per year

Countries citing papers authored by Elizabeth D. Brown

Since Specialization
Citations

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

Fields of papers citing papers by Elizabeth D. Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Elizabeth D. Brown

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

All Works

16 of 16 papers shown
#WorkIndexed citations
1
3D statistical neuroanatomical models from 305 MRI volumesbreakdown →
1015
2 113
3 8
4 19
5 21
6 11
7 65
8 35
9 16
10 32
11 13
12 10
13 15
14 235
15 118
16 24

About Elizabeth D. Brown

Elizabeth D. Brown is a scholar working on Hepatology, Transplantation and Radiology, Nuclear Medicine and Imaging, having authored 16 papers that have together received 1.8k indexed citations. Recurring topics across this work include MRI in cancer diagnosis (5 papers), Hepatocellular Carcinoma Treatment and Prognosis (4 papers) and Pediatric Urology and Nephrology Studies (3 papers). The work is most often cited by research in Cognitive Neuroscience (663 citations), Hepatology (259 citations) and Radiology, Nuclear Medicine and Imaging (618 citations). Elizabeth D. Brown has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include Rachel Kelly, Alan C. Evans, Terry M. Peters, D. Louis Collins, Richard C. Semelka, A S Bagley, Jeffrey J. Brown, Susan M. Ascher, Richard H. Patt and J. Patrick Shoenut. Their work appears in journals such as Radiology, Radiographics and Journal of Magnetic Resonance Imaging.

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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