Jonathan Nissanov

2.6k total citations
55 papers, 2.0k citations indexed

About

Jonathan Nissanov is a scholar working on Computer Vision and Pattern Recognition, Cognitive Neuroscience and Molecular Biology. According to data from OpenAlex, Jonathan Nissanov has authored 55 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Vision and Pattern Recognition, 13 papers in Cognitive Neuroscience and 12 papers in Molecular Biology. Recurrent topics in Jonathan Nissanov's work include Medical Image Segmentation Techniques (13 papers), Advanced MRI Techniques and Applications (9 papers) and Cell Image Analysis Techniques (8 papers). Jonathan Nissanov is often cited by papers focused on Medical Image Segmentation Techniques (13 papers), Advanced MRI Techniques and Applications (9 papers) and Cell Image Analysis Techniques (8 papers). Jonathan Nissanov collaborates with scholars based in United States, Israel and Spain. Jonathan Nissanov's co-authors include Robert C. Eaton, Randolf DiDomenico, Oleh J. Tretiak, Steven E. Arnold, David A. Bennett, John Q. Trojanowski, Thomas W. Mitchell, G. Allan Johnson, Boma Fubara and Alexandra Badea and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and NeuroImage.

In The Last Decade

Jonathan Nissanov

55 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan Nissanov United States 25 509 469 425 392 343 55 2.0k
Marleen Verhoye Belgium 43 1.4k 2.8× 621 1.3× 847 2.0× 2.1k 5.5× 105 0.3× 183 5.5k
W. B. Marks United States 19 753 1.5× 516 1.1× 553 1.3× 128 0.3× 125 0.4× 22 2.1k
Douglas J. Cook Canada 19 177 0.3× 374 0.8× 340 0.8× 223 0.6× 44 0.1× 58 1.7k
G. David Lange United States 25 329 0.6× 1.1k 2.4× 986 2.3× 118 0.3× 137 0.4× 36 2.5k
Peter J. Steenbergen Netherlands 23 181 0.4× 336 0.7× 310 0.7× 144 0.4× 524 1.5× 45 2.1k
Julie H. Sandell United States 29 1.5k 2.9× 1.4k 3.1× 1.6k 3.7× 200 0.5× 245 0.7× 49 3.8k
Jeremy F.P. Ullmann Australia 19 246 0.5× 264 0.6× 204 0.5× 252 0.6× 227 0.7× 35 1.2k
Pierre Lachapelle Canada 39 524 1.0× 2.6k 5.5× 1.3k 3.0× 1.1k 2.8× 149 0.4× 190 4.5k
Kiên Kiêu France 14 214 0.4× 529 1.1× 337 0.8× 85 0.2× 57 0.2× 30 1.9k
Joanne A. Matsubara Canada 36 526 1.0× 1.3k 2.7× 570 1.3× 779 2.0× 107 0.3× 131 3.3k

Countries citing papers authored by Jonathan Nissanov

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Nissanov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan Nissanov

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

All Works

20 of 20 papers shown
1.
Hawrylycz, Michael, Richard Baldock, Albert Burger, et al.. (2011). Digital Atlasing and Standardization in the Mouse Brain. PLoS Computational Biology. 7(2). e1001065–e1001065. 80 indexed citations
2.
Hawrylycz, Michael, Richard Baldock, Albert Burger, et al.. (2011). Correction: Digital Atlasing and Standardization in the Mouse Brain. PLoS Computational Biology. 7(2). 12 indexed citations
3.
Kiryati, Nahum, et al.. (2007). Atlas-Based Indexing of Brain Sections via 2-D to 3-D Image Registration. IEEE Transactions on Biomedical Engineering. 55(1). 147–156. 13 indexed citations
4.
Nissanov, Jonathan, et al.. (2006). Cryoplane fluorescence microscopy. 362–366. 4 indexed citations
5.
Lell, Bertrand, et al.. (2005). Symmetry-based 3D brain reconstruction. 2. 744–747. 4 indexed citations
6.
Schwartz, Eric D., Yingli Fan, Abbas F. Jawad, et al.. (2004). MRI diffusion coefficients in spinal cord correlate with axon morphometry. Neuroreport. 16(1). 73–76. 124 indexed citations
7.
Tretiak, Oleh J., et al.. (2004). Surface Alignment of an Elastic Body Using a Multiresolution Wavelet Representation. IEEE Transactions on Biomedical Engineering. 51(7). 1230–1241. 8 indexed citations
8.
Tretiak, Oleh J., et al.. (2003). Elastic 3-D alignment of rat brain histological images. IEEE Transactions on Medical Imaging. 22(11). 1480–1489. 39 indexed citations
9.
Tretiak, Oleh J., et al.. (2003). Design and implementation of software for assembly and browsing of 3D brain atlases. Computer Methods and Programs in Biomedicine. 74(1). 53–61. 22 indexed citations
10.
Bug, William & Jonathan Nissanov. (2003). A Guide to Building Image-Centric Databases. Neuroinformatics. 1(4). 359–378. 8 indexed citations
11.
Rosen, Glenn D., Nathan T. La Porte, Jonathan Nissanov, et al.. (2003). Informatics Center for Mouse Genomics: The Dissection of Complex Traits of the Nervous System. Neuroinformatics. 1(4). 327–342. 43 indexed citations
12.
Shumsky, Jed S., et al.. (2002). Differential effects of prenatal cocaine exposure on selected subunit mRNAs of the GABAA receptor in rabbit anterior cingulate cortex. Journal of Chemical Neuroanatomy. 24(4). 243–255. 3 indexed citations
13.
Mitchell, Thomas W., Elliott J. Mufson, Julie A. Schneider, et al.. (2002). Parahippocampal tau pathology in healthy aging, mild cognitive impairment, and early Alzheimer's disease. Annals of Neurology. 51(2). 182–189. 207 indexed citations
14.
Nissanov, Jonathan, et al.. (2001). Cryosectioning distortion reduction using tape support. Microscopy Research and Technique. 53(3). 239–240. 19 indexed citations
15.
Mitchell, Thomas W., Jonathan Nissanov, Liying Han, et al.. (2000). Novel Method to Quantify Neuropil Threads in Brains from Elders With or Without Cognitive Impairment. Journal of Histochemistry & Cytochemistry. 48(12). 1627–1637. 71 indexed citations
16.
Nissanov, Jonathan, et al.. (2000). Three‐dimensional imaging of the craniofacial complex. PubMed. 3(1). 46–50. 12 indexed citations
17.
Rioux, Lise, Jonathan Nissanov, & Jeffrey N. Joyce. (1998). Increased number of [125I] BH-substance p receptors in schizophrenia. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 22(8). 1295–1299. 7 indexed citations
18.
McEachron, Donald L., Jonathan Nissanov, & Oleh J. Tretiak. (1997). Region-specific tritium enrichment, and not differential -absorption, is the major cause of `quenching' in film autoradiography. Physics in Medicine and Biology. 42(6). 1121–1132. 2 indexed citations
19.
Nissanov, Jonathan & Donald L. McEachron. (1991). Advances in image processing for autoradiography. Journal of Chemical Neuroanatomy. 4(5). 329–342. 23 indexed citations
20.
Eaton, Robert C., Randolf DiDomenico, & Jonathan Nissanov. (1991). Role of the Mauthner Cell in Sensorimotor Integration by the Brain Stem Escape Network. Brain Behavior and Evolution. 37(5). 272–285. 139 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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