Michael Pienn

785 citations
22 papers · 588 · h-index 11

Impact in

Papers in

Michael Pienn

18 papers receiving 578 citations

Peers

Michael Pienn
Comparison fields: 5 of 36
  • Pulmonary and Respiratory Medicine 250
  • Computer Vision and Pattern Recognition 135
  • Internal Medicine 6
  • Radiology, Nuclear Medicine and Imaging 30
  • Pathology and Forensic Medicine 14
Replace Gideon A. Paul with:
Gideon A. Paul Canada
Meltem Gülsün Türkiye
Krit Dwivedi United Kingdom
Arveen A. Kalapara United States
Shonket Ray United States
Takuji Kiryu Japan
Archana T. Laroia United States
Gouthami Chintalapani United States
Wadim Wojciechowski Poland
Émilie Niaf France
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Citations per year

Countries citing papers authored by Michael Pienn

Since Specialization
Citations

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

Fields of papers citing papers by Michael Pienn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014178
2 2014128
3 201481
4 201631
5 201927
6 201925
7 201721
8 201320
9 201817
10 202313
11 202212
12 201811
13 201310
14 20155
15 20234
16 20243
17 20221
18 20221
19 20140
20 20140

About Michael Pienn

Michael Pienn is a scholar working on Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Internal Medicine, Pathology and Forensic Medicine and Nuclear Energy and Engineering, having authored 22 papers that have together received 588 indexed citations. Recurring topics across this work include Pulmonary Hypertension Research and Treatments (7 papers), Medical Image Segmentation Techniques (6 papers), Advanced Neural Network Applications (2 papers), Systemic Sclerosis and Related Diseases (1 paper), Venous Thromboembolism Diagnosis and Management (1 paper), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (1 paper) and Chronic Obstructive Pulmonary Disease (COPD) Research (1 paper). The work is most often cited by research in Pulmonary and Respiratory Medicine (250 citations), Computer Vision and Pattern Recognition (135 citations), Internal Medicine (6 citations), Radiology, Nuclear Medicine and Imaging (30 citations) and Pathology and Forensic Medicine (14 citations). Michael Pienn has collaborated with scholars based in Austria, Germany and United States. Frequent co-authors include Horst Olschewski, Gábor Kovács, Alexander Avian, Robert Naeije, Martin Urschler, Andrea Olschewski, Zoltán Bálint, Christian Payer, Rudolf Stollberger and Peter Kullnig. Their work appears in journals such as Medical Image Analysis, European Radiology, European Respiratory Journal, Frontiers in Physiology and Lara D. Veeken.

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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