Artur Przelaskowski

570 citations
46 papers · 260 · h-index 8

Impact in

Papers in

Artur Przelaskowski

36 papers receiving 230 citations

Peers

Artur Przelaskowski
Comparison fields: 5 of 60
  • Health Informatics 15
  • Computer Vision and Pattern Recognition 117
  • Neurology 22
  • Signal Processing 30
  • Radiology, Nuclear Medicine and Imaging 49
Replace Fandong Zhang with:
Fandong Zhang China
Meilu Zhu Hong Kong
Pedro C. Neto Portugal
Aaron Loh United States
Lisa Di Jorio Canada
Vijaya Kumar Koppula India
Xian Wu China
Abhishek Das India
G. R. Hemalakshmi India
Saleha Masood Pakistan
Artur Przelaskowski relative to Fandong Zhang China Fandong Zhang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Artur Przelaskowski

Since Specialization
Citations

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

Fields of papers citing papers by Artur Przelaskowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200647
2 202140
3
Segmentation and feature extraction for reliable classification of microcalcifications in digital mammograms
200326
4 200319
5 201518
6 202111
7 20018
8 20207
9 20086
10 20225
11 20175
12 20045
13 20135
14 20214
15 19984
16
Multiscale extraction of hypodensity in hyperacute stroke.
20074
17
Conceptual improvements in computer-aided diagnosis of acute stroke
20113
18 20153
19 20093
20
CT diagnosis of early stroke : the initial approach to the new CAD tool based on multiscale estimation of ischemia
20093

About Artur Przelaskowski

Artur Przelaskowski is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Signal Processing, having authored 46 papers that have together received 260 indexed citations. Recurring topics across this work include Advanced Data Compression Techniques (18 papers), Image and Signal Denoising Methods (15 papers), AI in cancer detection (8 papers), Digital Filter Design and Implementation (6 papers), Acute Ischemic Stroke Management (5 papers), Image Retrieval and Classification Techniques (5 papers), Advanced Image Fusion Techniques (5 papers) and Medical Image Segmentation Techniques (4 papers). The work is most often cited by research in Health Informatics (15 citations), Computer Vision and Pattern Recognition (117 citations), Neurology (22 citations), Signal Processing (30 citations) and Radiology, Nuclear Medicine and Imaging (49 citations). Artur Przelaskowski has collaborated with scholars based in Poland, Canada and Saudi Arabia. Frequent co-authors include Katarzyna Sklinda, Jerzy Walecki, Anna Wróblewska, Przemysław Biecek, Bartosz Mruk, Z. Papir, Mariusz Duplaga, Mikołaj Leszczuk, Mirosław Mazurek and Jiří Mazurek. Their work appears in journals such as Computers in Biology and Medicine, PeerJ, Multimedia Tools and Applications, IEEE Communications Magazine and International Journal of Approximate Reasoning.

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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