Jacob R. Glaser

957 total citations
12 papers, 613 citations indexed

About

Jacob R. Glaser is a scholar working on Biophysics, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Jacob R. Glaser has authored 12 papers receiving a total of 613 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Biophysics, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Molecular Biology. Recurrent topics in Jacob R. Glaser's work include Cell Image Analysis Techniques (9 papers), Medical Image Segmentation Techniques (4 papers) and Neurological disorders and treatments (2 papers). Jacob R. Glaser is often cited by papers focused on Cell Image Analysis Techniques (9 papers), Medical Image Segmentation Techniques (4 papers) and Neurological disorders and treatments (2 papers). Jacob R. Glaser collaborates with scholars based in United States, Germany and France. Jacob R. Glaser's co-authors include Edmund M. Glaser, Susan Tappan, Patrick R. Hof, Brian S. Eastwood, Amyaouch Bradaïa, Juha Yrjänheikki, Larry C. Park, David Howland, Ignacio Muñoz-Sanjuán and Bruno Buisson and has published in prestigious journals such as PLoS ONE, The Journal of Comparative Neurology and Computerized Medical Imaging and Graphics.

In The Last Decade

Jacob R. Glaser

11 papers receiving 604 citations

Peers

Jacob R. Glaser

CMN

BIOPH

NEURO

Daniel Fürth Sweden

Francisca Martínez Traub United States

Katherine S. Matho United States

Gülçin Pekkurnaz United States

J. J. Johannes Hjorth Sweden

Omar A. Ramírez Chile

Thomas M. Newpher United States

Christopher S. Bjornsson United States

Frederick B. Shipley United States

Arthur P.H. de Jong Netherlands

Daniel Fürth Sweden

Jacob R. Glaser

382 ×1.2

CMN

635 ×2.5

152 ×1.0

BIOPH

40 ×0.4

NEURO

353 ×3.6

Citations per year, relative to Jacob R. Glaser Jacob R. Glaser (= 1×) peers Daniel Fürth

Countries citing papers authored by Jacob R. Glaser

Since Specialization

Citations

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

Fields of papers citing papers by Jacob R. Glaser

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jacob R. Glaser. 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 Jacob R. Glaser. The network helps show where Jacob R. Glaser may publish in the future.

Co-authorship network of co-authors of Jacob R. Glaser

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

Brattain, Laura J., et al.. (2025). Topology-Preserving Deep Supervision for 3D Axon Centerline Segmentation Using Partially Annotated Data. PubMed. 2025. 1–5.

Gjesteby, Lars, M Snyder, Brian S. Eastwood, et al.. (2023). Self-Supervised Learning to Improve Topology-Optimized Axon Segmentation and Centerline Detection. PubMed. 2023. 1–4. 3 indexed citations

Tappan, Susan, et al.. (2021). A Comprehensive, FAIR File Format for Neuroanatomical Structure Modeling. Neuroinformatics. 20(1). 221–240. 4 indexed citations

Tappan, Susan, Brian S. Eastwood, Nathan O’Connor, et al.. (2019). Automatic navigation system for the mouse brain. The Journal of Comparative Neurology. 527(13). 2200–2211. 20 indexed citations

Eastwood, Brian S., Bryan M. Hooks, Ronald F. Paletzki, et al.. (2018). Whole mouse brain reconstruction and registration to a reference atlas with standard histochemical processing of coronal sections. The Journal of Comparative Neurology. 527(13). 2170–2178. 15 indexed citations

Dickstein, Dara L., Daniel R. Dickstein, William G.M. Janssen, et al.. (2016). Automatic Dendritic Spine Quantification from Confocal Data with Neurolucida 360. Current Protocols in Neuroscience. 77(1). 1.27.1–1.27.21. 57 indexed citations

Roussel, Nicolas, et al.. (2014). Robust tracking and quantification ofC. elegansbody shape and locomotion through coiling, entanglement, and omega bends. PubMed. 3(4). e982437–e982437. 37 indexed citations

Schmitz, Christoph, Brian S. Eastwood, Susan Tappan, et al.. (2014). Current automated 3D cell detection methods are not a suitable replacement for manual stereologic cell counting. Frontiers in Neuroanatomy. 8. 27–27. 48 indexed citations

O’Connor, Nathan, Susan Tappan, & Jacob R. Glaser. (2014). How to Prepare Neuroanatomical Image Data. Current Protocols in Neuroscience. 69(1). 1.21.1–14. 1 indexed citations

10.

Heikkinen, Taneli, Kimmo Lehtimäki, Nina Vartiainen, et al.. (2012). Characterization of Neurophysiological and Behavioral Changes, MRI Brain Volumetry and 1H MRS in zQ175 Knock-In Mouse Model of Huntington's Disease. PLoS ONE. 7(12). e50717–e50717. 188 indexed citations

11.

Glaser, Jacob R. & Edmund M. Glaser. (2000). Stereology, morphometry, and mapping: the whole is greater than the sum of its parts. Journal of Chemical Neuroanatomy. 20(1). 115–126. 76 indexed citations

12.

Glaser, Jacob R. & Edmund M. Glaser. (1990). Neuron imaging with neurolucida — A PC-based system for image combining microscopy. Computerized Medical Imaging and Graphics. 14(5). 307–317. 164 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.

Explore authors with similar magnitude of impact