Håkan Wieslander

420 total citations
9 papers, 247 citations indexed

About

Håkan Wieslander is a scholar working on Media Technology, Biophysics and Molecular Biology. According to data from OpenAlex, Håkan Wieslander has authored 9 papers receiving a total of 247 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Media Technology, 5 papers in Biophysics and 2 papers in Molecular Biology. Recurrent topics in Håkan Wieslander's work include Image Processing Techniques and Applications (5 papers), Cell Image Analysis Techniques (5 papers) and Advanced Vision and Imaging (2 papers). Håkan Wieslander is often cited by papers focused on Image Processing Techniques and Applications (5 papers), Cell Image Analysis Techniques (5 papers) and Advanced Vision and Imaging (2 papers). Håkan Wieslander collaborates with scholars based in Sweden, Australia and Finland. Håkan Wieslander's co-authors include Carolina Wählby, Philip J. Harrison, Ola Spjuth, Ida‐Maria Sintorn, Kimmo Kartasalo, Amit Suveer, Anna H. Klemm, Leslie Solorzano, Anindya Gupta and Johan Karlsson and has published in prestigious journals such as PLoS ONE, PLoS Computational Biology and Nanomedicine.

In The Last Decade

Håkan Wieslander

9 papers receiving 244 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Håkan Wieslander Sweden	6	98	74	65	41	39	9	247
Adityanarayanan Radhakrishnan United States	8	57 0.6×	57 0.8×	137 2.1×	27 0.7×	23 0.6×	14	282
Devin P. Sullivan United States	5	88 0.9×	34 0.5×	109 1.7×	21 0.5×	10 0.3×	10	230
Tim Scherr Germany	7	70 0.7×	57 0.8×	34 0.5×	57 1.4×	36 0.9×	17	156
Paolo Andreini Italy	10	38 0.4×	76 1.0×	28 0.4×	116 2.8×	43 1.1×	22	246
Aurora Sáez Spain	10	33 0.3×	105 1.4×	39 0.6×	41 1.0×	22 0.6×	21	293
Nicolas Quach United States	6	219 2.2×	71 1.0×	171 2.6×	63 1.5×	36 0.9×	8	506
Joshua Kangas United States	7	113 1.2×	46 0.6×	124 1.9×	37 0.9×	8 0.2×	11	255
Ervin Tasnádi Hungary	7	71 0.7×	43 0.6×	58 0.9×	36 0.9×	13 0.3×	13	178
Zan Armstrong United States	6	26 0.3×	65 0.9×	118 1.8×	43 1.0×	10 0.3×	8	281
Rickard Sjögren Sweden	9	119 1.2×	66 0.9×	66 1.0×	55 1.3×	97 2.5×	23	390

Countries citing papers authored by Håkan Wieslander

Since Specialization

Citations

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

Fields of papers citing papers by Håkan Wieslander

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Håkan Wieslander

This figure shows the co-authorship network connecting the top 25 collaborators of Håkan Wieslander. A scholar is included among the top collaborators of Håkan Wieslander based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Håkan Wieslander. Håkan Wieslander is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Harrison, Philip J., Ankit Gupta, Håkan Wieslander, et al.. (2023). Evaluating the utility of brightfield image data for mechanism of action prediction. PLoS Computational Biology. 19(7). e1011323–e1011323. 11 indexed citations

2.

Toor, Salman, Håkan Wieslander, Philip J. Harrison, et al.. (2021). Rapid development of cloud-native intelligent data pipelines for scientific data streams using the HASTE Toolkit. GigaScience. 10(3). 3 indexed citations

3.

Harrison, Philip J., Håkan Wieslander, Alan Sabirsh, et al.. (2021). Deep-Learning Models for Lipid Nanoparticle-Based Drug Delivery. Nanomedicine. 16(13). 1097–1110. 33 indexed citations

4.

Wieslander, Håkan, et al.. (2021). Learning to see colours: Biologically relevant virtual staining for adipocyte cell images. PLoS ONE. 16(10). e0258546–e0258546. 11 indexed citations

5.

Wieslander, Håkan, Carolina Wählby, & Ida‐Maria Sintorn. (2021). TEM image restoration from fast image streams. PLoS ONE. 16(2). e0246336–e0246336. 2 indexed citations

6.

Wieslander, Håkan, Philip J. Harrison, Gabriel Skogberg, et al.. (2020). Deep Learning With Conformal Prediction for Hierarchical Analysis of Large-Scale Whole-Slide Tissue Images. IEEE Journal of Biomedical and Health Informatics. 25(2). 371–380. 22 indexed citations

7.

Gupta, Anindya, Philip J. Harrison, Håkan Wieslander, et al.. (2018). Deep Learning in Image Cytometry: A Review. Cytometry Part A. 95(4). 366–380. 128 indexed citations

8.

Wieslander, Håkan, et al.. (2018). HarmonicIO: Scalable Data Stream Processing for Scientific Datasets. 879–882. 3 indexed citations

9.

Wieslander, Håkan, et al.. (2017). Deep Convolutional Neural Networks for Detecting Cellular Changes Due to Malignancy. KTH Publication Database DiVA (KTH Royal Institute of Technology). 82–89. 34 indexed citations

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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