Brian Krasner

400 citations
24 papers · 336 · h-index 7

Impact in

Papers in

Brian Krasner

22 papers receiving 318 citations

Peers

Brian Krasner
Comparison fields: 5 of 68
  • Radiology, Nuclear Medicine and Imaging 122
  • Computer Vision and Pattern Recognition 97
  • Artificial Intelligence 141
  • Pathology and Forensic Medicine 38
  • Equine 3
Replace Hong‐Ming Tsai with:
Hong‐Ming Tsai Taiwan
Cai Chang China
Michael Wels Germany
Adolf Lorenz Germany
Nasrin Ahmadinejad Iran
Arne Juette United Kingdom
Daniel Smutek Czechia
Liyan Lin China
Keewon Shin South Korea
Clifford Yang United States
Brian Krasner relative to Hong‐Ming Tsai Taiwan Hong‐Ming Tsai's profile →
Citations per field
00.5×2×3.5×
Hong‐Ming Tsai · 1×
Citations per year

Countries citing papers authored by Brian Krasner

Since Specialization
Citations

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

Fields of papers citing papers by Brian Krasner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993189
2 199030
3 199521
4 199421
5 199013
6
Quantitative sonographic feature analysis of clinical infant hypoxia: a pilot study.
199613
7 199211
8 19946
9 19896
10 19915
11 19923
12
Rectal bleeding and hemorrhage in diverticulosis and diverticulitis.
19623
13 19942
14 19892
15 19922
16 19892
17 19932
18 19951
19 19921
20 19881

About Brian Krasner

Brian Krasner is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Pulmonary and Respiratory Medicine and Surgery, having authored 24 papers that have together received 336 indexed citations. Recurring topics across this work include Advanced Data Compression Techniques (7 papers), AI in cancer detection (6 papers), Medical Imaging Techniques and Applications (4 papers), Digital Radiography and Breast Imaging (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Ultrasound Imaging and Elastography (2 papers), Medical Image Segmentation Techniques (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (122 citations), Computer Vision and Pattern Recognition (97 citations), Artificial Intelligence (141 citations), Pathology and Forensic Medicine (38 citations) and Equine (3 citations). Brian Krasner has collaborated with scholars based in United States, Portugal and South Sudan. Frequent co-authors include Seong K. Mun, Brian S. Garra, Steven C. Horii, Robert K. Zeman, Susan M. Ascher, S.-C.B. Lo, Shih‐Chung B. Lo, Lori L. Barr, J W Allison and Cuong C. Nguyen. Their work appears in journals such as Journal of Digital Imaging, Radiographics, Ultrasonic Imaging, IEEE Transactions on Medical Imaging and Gastrointestinal Endoscopy.

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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