Marcos Salganicoff

4.5k total citations
56 papers, 1.2k citations indexed

About

Marcos Salganicoff is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Marcos Salganicoff has authored 56 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Radiology, Nuclear Medicine and Imaging, 19 papers in Artificial Intelligence and 13 papers in Control and Systems Engineering. Recurrent topics in Marcos Salganicoff's work include Radiomics and Machine Learning in Medical Imaging (14 papers), Lung Cancer Diagnosis and Treatment (11 papers) and Robot Manipulation and Learning (9 papers). Marcos Salganicoff is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (14 papers), Lung Cancer Diagnosis and Treatment (11 papers) and Robot Manipulation and Learning (9 papers). Marcos Salganicoff collaborates with scholars based in United States, Germany and United Kingdom. Marcos Salganicoff's co-authors include Arun V. Krishnan, Le Lü, M. Ali Akber Dewan, Toshiro Kubota, Anna Jerebko, George L. Gerstein, Matthias Wolf, Jinbo Bi, Joachim E. Wildberger and Marco Das and has published in prestigious journals such as IEEE Transactions on Medical Imaging, American Journal of Roentgenology and Computer.

In The Last Decade

Marcos Salganicoff

54 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marcos Salganicoff United States 22 577 426 331 247 210 56 1.2k
Jared Dunnmon United States 14 284 0.5× 74 0.2× 282 0.9× 67 0.3× 150 0.7× 23 908
Jai Prashanth Rao Singapore 8 555 1.0× 96 0.2× 515 1.6× 356 1.4× 190 0.9× 19 1.3k
Bikesh Kumar Singh India 22 567 1.0× 219 0.5× 583 1.8× 304 1.2× 152 0.7× 100 1.4k
Manuel G. Penedo Spain 23 1.0k 1.8× 172 0.4× 273 0.8× 594 2.4× 204 1.0× 121 1.9k
Ari Seff United States 9 588 1.0× 192 0.5× 406 1.2× 294 1.2× 197 0.9× 10 1.0k
André Bauer Germany 20 258 0.4× 113 0.3× 125 0.4× 41 0.2× 354 1.7× 83 1.4k
Martin Lillholm Denmark 17 479 0.8× 284 0.7× 572 1.7× 281 1.1× 170 0.8× 49 1.4k
Burak Acar Türkiye 18 864 1.5× 194 0.5× 355 1.1× 481 1.9× 178 0.8× 65 2.2k
Shan Yang Switzerland 12 466 0.8× 125 0.3× 151 0.5× 331 1.3× 227 1.1× 43 1.1k
Hyunkwang Lee United States 13 450 0.8× 102 0.2× 451 1.4× 419 1.7× 270 1.3× 15 1.7k

Countries citing papers authored by Marcos Salganicoff

Since Specialization
Citations

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

Fields of papers citing papers by Marcos Salganicoff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marcos Salganicoff

This figure shows the co-authorship network connecting the top 25 collaborators of Marcos Salganicoff. A scholar is included among the top collaborators of Marcos Salganicoff 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 Marcos Salganicoff. Marcos Salganicoff 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.
Liao, Shu, et al.. (2016). Automatic Lumbar SpondylolisthesisMeasurement in CT Images. IEEE Transactions on Medical Imaging. 35(7). 1658–1669. 15 indexed citations
2.
Godoy, Myrna C. B., Tae Jung Kim, Charles S. White, et al.. (2012). Benefit of Computer-Aided Detection Analysis for the Detection of Subsolid and Solid Lung Nodules on Thin- and Thick-Section CT. American Journal of Roentgenology. 200(1). 74–83. 46 indexed citations
3.
Liu, Meizhu, Le Lü, Xiaojing Ye, Shipeng Yu, & Marcos Salganicoff. (2011). Sparse Classification for Computer Aided Diagnosis Using Learned Dictionaries. Lecture notes in computer science. 14(Pt 3). 41–48. 31 indexed citations
4.
Liu, Meizhu, Le Lü, Jinbo Bi, et al.. (2011). Robust Large Scale Prone-Supine Polyp Matching Using Local Features: A Metric Learning Approach. Lecture notes in computer science. 14(Pt 3). 75–82. 8 indexed citations
5.
Mang, Thomas, Luca Bogoni, Marcos Salganicoff, et al.. (2011). Computer-Aided Detection of Colorectal Polyps in CT Colonography With and Without Fecal Tagging. Investigative Radiology. 47(2). 99–108. 17 indexed citations
6.
Jun, Ma, Le Lü, Yiqiang Zhan, et al.. (2010). Hierarchical Segmentation and Identification of Thoracic Vertebra Using Learning-Based Edge Detection and Coarse-to-Fine Deformable Model. Lecture notes in computer science. 13(Pt 1). 19–27. 63 indexed citations
7.
Lü, Le, M. Ali Akber Dewan, Albert Y. Chen, et al.. (2009). Multi-level Ground Glass Nodule Detection and Segmentation in CT Lung Images. Lecture notes in computer science. 12(Pt 2). 715–723. 40 indexed citations
8.
Lü, Le, Matthias Wolf, Jianming Liang, et al.. (2009). A Two-Level Approach Towards Semantic Colon Segmentation: Removing Extra-Colonic Findings. Lecture notes in computer science. 12(Pt 2). 1009–1016. 15 indexed citations
9.
Das, Marco, Georg Mühlenbruch, Annemarie Bakai, et al.. (2008). Computer-aided detection of pulmonary embolism: Influence on radiologists’ detection performance with respect to vessel segments. European Radiology. 18(7). 1350–1355. 43 indexed citations
10.
Das, Marco, Georg Mühlenbruch, Andreas H. Mahnken, et al.. (2008). Performance evaluation of a computer-aided detection algorithm for solid pulmonary nodules in low-dose and standard-dose MDCT chest examinations and its influence on radiologists. British Journal of Radiology. 81(971). 841–847. 34 indexed citations
11.
Buhmann, Sonja, Peter Herzog, Liang Jin, et al.. (2007). Clinical Evaluation of a Computer-Aided Diagnosis (CAD) Prototype for the Detection of Pulmonary Embolism. Academic Radiology. 14(6). 651–658. 42 indexed citations
12.
Qiu, Wu, Marcos Salganicoff, Arun V. Krishnan, Donald S. Fussell, & Mia K. Markey. (2006). Interactive lesion segmentation on dynamic contrast enhanced breast MRI using a Markov model. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6144. 61444M–61444M. 26 indexed citations
13.
Wolf, Matthias, Arun V. Krishnan, Marcos Salganicoff, et al.. (2005). CAD performance analysis for pulmonary nodule detection on thin-slice MDCT scans. International Congress Series. 1281. 1104–1108. 3 indexed citations
14.
Salganicoff, Marcos & Růžena Bajcsy. (2003). Robotic sensorimotor learning in continuous domains. 2045–2050.
15.
Camus, Ted, et al.. (2002). Sensar...secure/sup TM/ Iris identification system. 254–255. 2 indexed citations
16.
Rahman, Tariq, et al.. (1996). Calibration of Closed Loop Controllers for Setting Impedances in Force-Reflecting Systems. Dynamic Systems and Control. 593–600. 2 indexed citations
17.
Salganicoff, Marcos, Lyle Ungar, & Ruzena Bajcsy. (1996). Active learning for vision-based robot grasping. Machine Learning. 23(2-3). 251–278. 43 indexed citations
18.
Salganicoff, Marcos & Růžena Bajcsy. (1991). Sensorimotor Learning Using Active Perception in Continuous Domains. ScholarlyCommons (University of Pennsylvania). 4 indexed citations
19.
Salganicoff, Marcos, et al.. (1989). Receptive Fields for the Determination of Textured Surface Inclination. ScholarlyCommons (University of Pennsylvania). 2 indexed citations
20.
Gochin, Paul M., et al.. (1988). Unsupervised waveform classification for multi-neuron recordings: a real-time, software-based system. II. Performance comparison to other sorters. Journal of Neuroscience Methods. 25(3). 189–196. 36 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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