Lior Weizman

41 total papers · 560 total citations
33 papers, 412 citations indexed

About

Lior Weizman is a scholar working on Radiology, Nuclear Medicine and Imaging, Computational Mechanics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Lior Weizman has authored 33 papers receiving a total of 412 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Computational Mechanics and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Lior Weizman's work include Sparse and Compressive Sensing Techniques (10 papers), Advanced MRI Techniques and Applications (9 papers) and Medical Imaging Techniques and Applications (7 papers). Lior Weizman is often cited by papers focused on Sparse and Compressive Sensing Techniques (10 papers), Advanced MRI Techniques and Applications (9 papers) and Medical Imaging Techniques and Applications (7 papers). Lior Weizman collaborates with scholars based in Israel, United Kingdom and United States. Lior Weizman's co-authors include Yonina C. Eldar, Jacob Goldberger, Dafna Ben Bashat, Leo Joskowicz, Liat Ben‐Sira, Shlomi Constantini, Assaf Tal, Ben Shofty, João F. C. Mota and Miguel R. D. Rodrigues and has published in prestigious journals such as International Journal of Remote Sensing, Medical Physics and Medical Image Analysis.

In The Last Decade

Lior Weizman

33 papers receiving 400 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Lior Weizman	164	119	77	70	64	33	412
Daniel Goldberg‐Zimring	213 1.3×	96 0.8×	41 0.5×	14 0.2×	11 0.2×	16	481
Neculai Archip	200 1.2×	205 1.7×	15 0.2×	18 0.3×	36 0.6×	23	422
Nicolas Wiest-Daesslé	280 1.7×	197 1.7×	18 0.2×	13 0.2×	48 0.8×	16	484
Xinyuan Zhang	305 1.9×	105 0.9×	11 0.1×	21 0.3×	26 0.4×	36	471
Carlo Ciulla	261 1.6×	94 0.8×	76 1.0×	32 0.5×	10 0.2×	39	444
Carole Frindel	200 1.2×	36 0.3×	42 0.5×	96 1.4×	5 0.1×	49	468
Fernando Pérez‐García	220 1.3×	102 0.9×	42 0.5×	19 0.3×	4 0.1×	18	484
Abhirup Banerjee	200 1.2×	132 1.1×	13 0.2×	24 0.3×	33 0.5×	50	457
Nagesh K. Subbanna	118 0.7×	219 1.8×	16 0.2×	40 0.6×	4 0.1×	17	444
Saad Nadeem	164 1.0×	90 0.8×	60 0.8×	13 0.2×	35 0.5×	45	485

Countries citing papers authored by Lior Weizman

Since Specialization

Citations

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

Fields of papers citing papers by Lior Weizman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lior Weizman

This figure shows the co-authorship network connecting the top 25 collaborators of Lior Weizman. A scholar is included among the top collaborators of Lior Weizman 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 Lior Weizman. Lior Weizman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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