Daniela Ushizima

2.0k citations
85 papers · 1.2k · h-index 22

Impact in

Papers in

Daniela Ushizima

80 papers receiving 1.2k citations

Peers

Daniela Ushizima
Comparison fields: 5 of 125
  • Biophysics 128
  • Computer Vision and Pattern Recognition 392
  • Artificial Intelligence 420
  • Structural Biology 16
  • Radiology, Nuclear Medicine and Imaging 248
Replace Gregor Urban with:
Gregor Urban United States
Zhihao Wu China
Teresa Mendonça Portugal
Kevin de Haan United States
Jovan G. Brankov United States
Liangqiong Qu China
Pablo Márquez-Neila Switzerland
Yanbo Zhang China
Guanglei Wang China
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Citations per year

Countries citing papers authored by Daniela Ushizima

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Ushizima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 85 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016116
2 201987
3 201952
4 201850
5 200940
6 202138
7 201236
8 202036
9
Segmentation of subcellular compartments combining superpixel representation with Voronoi diagrams
201535
10 202133
11 201833
12 202332
13 202130
14 200529
15 201629
16 201927
17 201026
18 201626
19 202326
20 202124

About Daniela Ushizima

Daniela Ushizima is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Biophysics, Radiology, Nuclear Medicine and Imaging and Biomedical Engineering, having authored 85 papers that have together received 1.2k indexed citations. Recurring topics across this work include AI in cancer detection (21 papers), Medical Image Segmentation Techniques (18 papers), Cell Image Analysis Techniques (17 papers), Digital Imaging for Blood Diseases (12 papers), Medical Imaging Techniques and Applications (9 papers), Cervical Cancer and HPV Research (9 papers), Advanced X-ray and CT Imaging (6 papers) and Image Retrieval and Classification Techniques (6 papers). The work is most often cited by research in Biophysics (128 citations), Computer Vision and Pattern Recognition (392 citations), Artificial Intelligence (420 citations), Structural Biology (16 citations) and Radiology, Nuclear Medicine and Imaging (248 citations). Daniela Ushizima has collaborated with scholars based in United States, Brazil and Canada. Frequent co-authors include Andrea Bianchi, Cláudia Martins Carneiro, F.N.S. Medeiros, Fátima N. S. de Medeiros, Mariana T. Rezende, Romuere Silva, Flávio H. D. Araújo, Dilworth Y. Parkinson, Zhi Lu and Alexander Hexemer. Their work appears in journals such as Scientific Reports, Cement and Concrete Research, Journal of Synchrotron Radiation, Expert Systems with Applications and Scientific Data.

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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