B. Wein

2.3k citations
90 papers · 1.5k indexed · h-index 17

B. Wein

87 papers receiving 1.4k citations

Peers

B. Wein
Comparison fields: 5 of 119
  • Computer Vision and Pattern Recognition 748
  • Artificial Intelligence 406
  • Radiology, Nuclear Medicine and Imaging 290
  • Speech and Hearing 67
  • Health Informatics 12
Replace Premal A. Patel with:
Premal A. Patel United Kingdom
Jean‐Nicolas Dacher France
Lynn S. Broderick United States
Oğuz Dıcle Türkiye
Xiangrong Zhou Japan
Akira Furukawa Japan
Hiroyuki Yoshida United States
Andrea Esposito Italy
Saher Burhan Shaker Denmark
Alexander Seitel Germany
B. Wein relative to Premal A. Patel United Kingdom Premal A. Patel's profile →
Citations per field
00.5×10×16.8×
Premal A. Patel · 1×
Citations per year

Countries citing papers authored by B. Wein

Since Specialization
Citations

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

Fields of papers citing papers by B. Wein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20068
2 2003101
3 20037
4 2002105
5
A distributed architecture for content-based image retrieval in medical applications
20028
6
Multi-slice CT for visualization of pulmonary embolism using perfusion weighted color maps
20022
7
Classification of radiographs in the 'image retrieval in medical applications' - system (IRMA)
20009
8 200017
9 19994
10 19982
11 19973
12 19973
13 199779
14 19952
15 19941
16 19941
17 19942
18 199313
19 19934
20 199130

About B. Wein

B. Wein is a scholar working on Speech and Hearing, Computer Vision and Pattern Recognition and Radiology, Nuclear Medicine and Imaging, having authored 90 papers that have together received 1.5k indexed citations. Recurring topics across this work include Image Retrieval and Classification Techniques (19 papers), Voice and Speech Disorders (10 papers), Advanced Image and Video Retrieval Techniques (10 papers), AI in cancer detection (9 papers), Tracheal and airway disorders (8 papers), Dysphagia Assessment and Management (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Radiation Dose and Imaging (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (748 citations), Artificial Intelligence (406 citations) and Radiology, Nuclear Medicine and Imaging (290 citations). B. Wein has collaborated with scholars based in Germany, United States and Belgium. Frequent co-authors include Thomas Lehmann, Henning Schubert, Daniel Keysers, Michael Kohnen, Hermann Ney, Klaus Spitzer, Mark Oliver Güld, Christian Thies, Benedikt Fischer and Joerg Bredno. Their work appears in journals such as RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren, Investigative Radiology, Ultraschall in der Medizin - European Journal of Ultrasound, Folia Phoniatrica et Logopaedica and Journal of Digital 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026