Manasi Datar

666 citations
16 papers · 238 · h-index 10

Impact in

Papers in

Manasi Datar

15 papers receiving 232 citations

Peers

Manasi Datar
Comparison fields: 5 of 55
  • Geometry and Topology 35
  • Computer Vision and Pattern Recognition 82
  • Radiology, Nuclear Medicine and Imaging 54
  • Orthopedics and Sports Medicine 20
  • Biophysics 10
Replace Estanislao Oubel with:
Estanislao Oubel United States
Jared Vicory United States
Pietro Gori France
Heiko Seim Germany
René Donner Austria
Alexandre Bône France
Pascal Cachier France
Joshua V. Stough United States
Jiřı́ Hladůvka Austria
Gilberto Zamora United States
Manasi Datar relative to Estanislao Oubel United States Estanislao Oubel's profile →
Citations per field
00.5×1.5×1.8×
Estanislao Oubel · 1×
Citations per year

Countries citing papers authored by Manasi Datar

Since Specialization
Citations

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

Fields of papers citing papers by Manasi Datar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Manasi Datar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Manasi Datar Line = papers co-authored together Manasi Datar links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 201369
2 200839
3 200925
4 201218
5 202215
6 201113
7 201212
8 201311
9 201211
10 201511
11 20086
12 20064
13 20161
14 20061
15
GPU Accelerated Particle System for Triangulated Surface Meshes
20091
16
NATURAL SCENE SEGMENTATION BASED ON INFORMATION FUSION AND HIERARCHICAL SELF-ORGANIZING MAPS
20051

About Manasi Datar

Manasi Datar is a scholar working on Computer Vision and Pattern Recognition, Geometry and Topology, Computational Mechanics, Artificial Intelligence and Computer Graphics and Computer-Aided Design, having authored 16 papers that have together received 238 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (7 papers), 3D Shape Modeling and Analysis (6 papers), Morphological variations and asymmetry (6 papers), Image Retrieval and Classification Techniques (3 papers), Computer Graphics and Visualization Techniques (3 papers), Image Processing and 3D Reconstruction (2 papers), AI in cancer detection (2 papers) and Computational Geometry and Mesh Generation (1 paper). The work is most often cited by research in Geometry and Topology (35 citations), Computer Vision and Pattern Recognition (82 citations), Radiology, Nuclear Medicine and Imaging (54 citations), Orthopedics and Sports Medicine (20 citations) and Biophysics (10 citations). Manasi Datar has collaborated with scholars based in United States, Germany and India. Frequent co-authors include Ross Whitaker, Elizabeth Jurrus, H. E. Cline, Dirk Padfield, Michael D. Harris, Christopher L. Peters, Andrew E. Anderson, Joshua Cates, Martin Styner and Beatriz Paniagua. Their work appears in journals such as Journal of Orthopaedic Research®, Radiation Oncology, International Journal of Computer Assisted Radiology and Surgery, Lecture notes in computer science and Advances in intelligent systems research.

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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