Boris Escalante‐Ramírez

1.2k total citations
106 papers, 726 citations indexed

About

Boris Escalante‐Ramírez is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Boris Escalante‐Ramírez has authored 106 papers receiving a total of 726 indexed citations (citations by other indexed papers that have themselves been cited), including 67 papers in Computer Vision and Pattern Recognition, 24 papers in Media Technology and 17 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Boris Escalante‐Ramírez's work include Medical Image Segmentation Techniques (34 papers), Image and Signal Denoising Methods (29 papers) and Advanced Image Fusion Techniques (18 papers). Boris Escalante‐Ramírez is often cited by papers focused on Medical Image Segmentation Techniques (34 papers), Image and Signal Denoising Methods (29 papers) and Advanced Image Fusion Techniques (18 papers). Boris Escalante‐Ramírez collaborates with scholars based in Mexico, Spain and United States. Boris Escalante‐Ramírez's co-authors include Rodrigo Nava, José Luis Silván-Cárdenas, Gabriel Cristóbal, Rafael Redondo, Jean-Bernard Martens, Óscar Déniz, Gloria Bueno, Ernesto Moya-Albor, Fernando Arámbula Cosı́o and Tomás Escobar Rodríguez and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Image Processing and IEEE Access.

In The Last Decade

Boris Escalante‐Ramírez

97 papers receiving 684 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Boris Escalante‐Ramírez Mexico 14 302 183 118 87 78 106 726
J. Serra France 17 642 2.1× 167 0.9× 42 0.4× 40 0.5× 102 1.3× 58 1.1k
Ping‐Sung Liao Taiwan 4 374 1.2× 112 0.6× 82 0.7× 66 0.8× 98 1.3× 8 732
Linwei Fan China 14 538 1.8× 323 1.8× 92 0.8× 78 0.9× 106 1.4× 44 896
Dominique Brunet France 11 286 0.9× 135 0.7× 51 0.4× 61 0.7× 48 0.6× 44 658
Pascal Getreuer United States 15 648 2.1× 240 1.3× 76 0.6× 83 1.0× 82 1.1× 28 996
Rama Krishna Gorthi India 13 695 2.3× 239 1.3× 53 0.4× 67 0.8× 106 1.4× 56 941
Wenxian Zheng China 6 413 1.4× 234 1.3× 88 0.7× 110 1.3× 89 1.1× 11 735
Said Pertuz Colombia 11 384 1.3× 458 2.5× 118 1.0× 118 1.4× 99 1.3× 47 889
Hiêp Luong Belgium 17 514 1.7× 252 1.4× 83 0.7× 77 0.9× 67 0.9× 98 841
Nikolay Petkov Bulgaria 9 496 1.6× 174 1.0× 76 0.6× 43 0.5× 126 1.6× 55 895

Countries citing papers authored by Boris Escalante‐Ramírez

Since Specialization
Citations

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

Fields of papers citing papers by Boris Escalante‐Ramírez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Boris Escalante‐Ramírez. 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 Boris Escalante‐Ramírez. The network helps show where Boris Escalante‐Ramírez may publish in the future.

Co-authorship network of co-authors of Boris Escalante‐Ramírez

This figure shows the co-authorship network connecting the top 25 collaborators of Boris Escalante‐Ramírez. A scholar is included among the top collaborators of Boris Escalante‐Ramírez 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 Boris Escalante‐Ramírez. Boris Escalante‐Ramírez 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.
2.
Montoya, Fernando, Paul Hernández‐Herrera, Hermes Gadêlha, et al.. (2024). Feature-based 3D+t descriptors of hyperactivated human sperm beat patterns. Heliyon. 10(5). e26645–e26645. 2 indexed citations
3.
Ramos, Rodrigo Pereira, et al.. (2024). Minimal FCN for image segmentation. 8–8.
4.
Escalante‐Ramírez, Boris, et al.. (2023). Removing Zero Variance Units of Deep Models for COVID-19 Detection. IEEE Access. 11. 26521–26529. 1 indexed citations
5.
Vallejo, Enrique, et al.. (2021). A multiphase texture-based model of active contours assisted by a convolutional neural network for automatic CT and MRI heart ventricle segmentation. Computer Methods and Programs in Biomedicine. 211. 106373–106373. 3 indexed citations
6.
Moya-Albor, Ernesto, et al.. (2020). 3D Hermite Transform Optical Flow Estimation in Left Ventricle CT Sequences. Sensors. 20(3). 595–595. 4 indexed citations
7.
Escalante‐Ramírez, Boris, et al.. (2018). Towards a Representation of Enterprise Architecture based on Zachman Framework through OMG Standards (S).. Software Engineering and Knowledge Engineering. 1 indexed citations
8.
Escalante‐Ramírez, Boris, et al.. (2017). A 3D Hermite-based multiscale local active contour method with elliptical shape constraints for segmentation of cardiac MR and CT volumes. Medical & Biological Engineering & Computing. 56(5). 833–851. 7 indexed citations
9.
Nava, Rodrigo, et al.. (2017). Left ventricle Hermite-based segmentation. Computers in Biology and Medicine. 87. 236–249. 7 indexed citations
10.
Moya-Albor, Ernesto, et al.. (2016). Segmentation and optical flow estimation in cardiac CT sequences based on a spatiotemporal PDM with a correction scheme and the Hermite transform. Computers in Biology and Medicine. 69. 189–202. 10 indexed citations
11.
Nava, Rodrigo, et al.. (2015). Feature ensemble for quantitative analysis of emphysema in CT imaging. 1–4. 9 indexed citations
12.
Marcos, J. Víctor, Rodrigo Nava, Gabriel Cristóbal, et al.. (2014). Automated pollen identification using microscopic imaging and texture analysis. Micron. 68. 36–46. 66 indexed citations
13.
Escalante‐Ramírez, Boris, et al.. (2014). Steganography in Audio Files by Hermite Transform. Applied Mathematics & Information Sciences. 8(3). 959–966. 5 indexed citations
14.
Escalante‐Ramírez, Boris, et al.. (2013). VO2 and VCO2 variabilities through indirect calorimetry instrumentation. SpringerPlus. 2(1). 688–688. 4 indexed citations
15.
Mateos-Pérez, J.M., Rafael Redondo, Rodrigo Nava, et al.. (2012). Comparative evaluation of autofocus algorithms for a real‐time system for automatic detection of Mycobacterium tuberculosis. Cytometry Part A. 81A(3). 213–221. 38 indexed citations
16.
Redondo, Rafael, Gloria Bueno, Rodrigo Nava, et al.. (2012). Autofocus evaluation for brightfield microscopy pathology. Journal of Biomedical Optics. 17(3). 36008–36008. 53 indexed citations
17.
Escalante‐Ramírez, Boris, et al.. (2006). Remote Sensing Image Fusion with a Multiresolution Directional-Oriented Image Transform Based on Gaussian Derivatives. AIP conference proceedings. 860. 178–187. 1 indexed citations
18.
Silván-Cárdenas, José Luis & Boris Escalante‐Ramírez. (2006). The multiscale Hermite transform for local orientation analysis. IEEE Transactions on Image Processing. 15(5). 1236–1253. 36 indexed citations
19.
Sacristán, E., et al.. (2005). Steady State Condition in the Measurement of VO<inf>2</inf>and VCO<inf>2</inf>by Indirect Calorimetry. PubMed. 2005. 7773–7776. 6 indexed citations
20.
Escalante‐Ramírez, Boris, et al.. (1997). Applications of Polynomial Transforms in Astronomical Image Restoration and Deconvolution. 33. 173–185. 1 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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