Mona K. Garvin
About
In The Last Decade
Mona K. Garvin
127 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Ophthalmology 4.2k
- Radiology, Nuclear Medicine and Imaging 4.1k
- Biomedical Engineering 1.3k
- Computer Vision and Pattern Recognition 949
- Neurology 415
Countries citing papers authored by Mona K. Garvin
This map shows the geographic impact of Mona K. Garvin'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 Mona K. Garvin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mona K. Garvin more than expected).
Fields of papers citing papers by Mona K. Garvin
This network shows the impact of papers produced by Mona K. Garvin. 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 Mona K. Garvin. The network helps show where Mona K. Garvin may publish in the future.
Co-authorship network of co-authors of Mona K. Garvin
This figure shows the co-authorship network connecting the top 25 collaborators of Mona K. Garvin. A scholar is included among the top collaborators of Mona K. Garvin 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 Mona K. Garvin. Mona K. Garvin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Title | Journal | Authors | Indexed citations |
|---|---|---|---|---|
| 1 | Macular patterns of neuronal and visual field loss in recovered optic neuritis identified by machine learning | Scientific Reports | Jui-Kai Wang, Tobias Elze et al. | 2 |
| 2 | Classifying and quantifying changes in papilloedema using machine learning | BMJ Neurology Open | Tobias Elze, Mona K. Garvin et al. | 2 |
| 3 | Utility of Spectral-Domain Optical Coherence Tomography in Differentiating Papilledema From Pseudopapilledema: A Prospective Longitudinal Study | Journal of Neuro-Ophthalmology | Maxwell Pistilli, Anita Kohli et al. | 10 |
| 4 | Differentiation between papilledema and nonarteritic anterior ischemic optic neuropathy using retinal layer shape and regional volume features in spectral-domain optical coherence tomography | Investigative Ophthalmology & Visual Science | Jui-Kai Wang, Matthew J. Thurtell et al. | 0 |
| 5 | Three-Dimensional Bruch’s Membrane Shape Model in Cases of Papilledema | Investigative Ophthalmology & Visual Science | Jui-Kai Wang, Randy H. Kardon et al. | 1 |
| 6 | Multimodal Graph-Theoretic Approach for Segmentation of the Internal Limiting Membrane at the Optic Nerve Head | Mohammad Saleh Miri, Michael D. Abràmoff et al. | 2 | |
| 7 | Retinal Ganglion Cell Layer Thinning and Vision Outcome in NAION and Optic Neuritis over Six Months | Investigative Ophthalmology & Visual Science | Jui-Kai Wang, Mark J. Kupersmith et al. | 2 |
| 8 | Retinal thinning in mice with streptozotocin-induced diabetes mellitus | Investigative Ophthalmology & Visual Science | Murat Küçükevcilioğlu, Woojin Jeong et al. | 2 |
| 9 | Retinal thickness changes in mice with streptozotocin-induced diabetes mellitus quantified using an enhanced Iowa Reference Algorithm | Investigative Ophthalmology & Visual Science | Woo‐Jin Jeong, Michael D. Abràmoff et al. | 1 |
| 10 | Prevalence of Structural Abnormalities of the Retinal Nerve Fiber Layer (RNFL) and Ganglion Cell Layer Complex (GCLC) by OCT in Veterans with Traumatic Brain Injury (TBI) | Investigative Ophthalmology & Visual Science | Randy H. Kardon, Mona K. Garvin et al. | 5 |
| 11 | Segmentation of Multiple Intra-retinal Surfaces in Volumetric SD-OCT Images of Mouse Eyes Using an Improved Iowa Reference Algorithm | Investigative Ophthalmology & Visual Science | Bhavna Antony, Michael D. Abràmoff et al. | 2 |
| 12 | Reproducibility of SD-OCT-Based Ganglion-Cell-Complex-Layer Thickness in Early Glaucoma using Commercial and Custom Segmentation Algorithms | Investigative Ophthalmology & Visual Science | Mona K. Garvin, Kyungmoo Lee et al. | 3 |
| 13 | Early Retinal Ganglion Cell Layer Thinning Due to Acute NAION and Optic Neuritis | Investigative Ophthalmology & Visual Science | Mark J. Kupersmith, Mona K. Garvin et al. | 1 |
| 14 | Automated Detection Of Retinal Hemorrhages In Malarial Retinopathy | Investigative Ophthalmology & Visual Science | Mona K. Garvin, Joseph M. Reinhardt et al. | 1 |
| 15 | Comparison of an Automated Method for Volumetric Quantification of Papilledema with the Frisén Scale | Investigative Ophthalmology & Visual Science | Jui-Kai Wang, Randy H. Kardon et al. | 1 |
| 16 | Automated Intraretinal Layer Segmentation of 3-D Macular OCT Scans Using a Multiscale Graph Search | Investigative Ophthalmology & Visual Science | Kwangwon Lee, Mona K. Garvin et al. | 2 |
| 17 | Automated Method for the Flattening of Optical Coherence Tomography Images | Investigative Ophthalmology & Visual Science | Bhavna Antony, Li Tang et al. | 1 |
| 18 | Automated Measurement of Optic Nerve Head Shape From Stereo Color Photographs of the Optic Disc: Validation With SD-OCT | Investigative Ophthalmology & Visual Science | Li Tang, Young H. Kwon et al. | 1 |
| 19 | Automated Segmentation of the Retinal Vasculature in 3D Optical Coherence Tomography Images | Investigative Ophthalmology & Visual Science | Meindert Niemeijer, Milan Sonka et al. | 3 |
| 20 | Three-Dimensional Analysis of SD OCT: Thickness Assessment of Six Macular Layers in Normal Subjects | Investigative Ophthalmology & Visual Science | Mona K. Garvin, Milan Sonka et al. | 2 |
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.