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Luis Carlos Rivera Monroy, M. Sc.

Luis Carlos Rivera Monroy, M. Sc.

Researcher

Chair of Computer Science 5 (Pattern Recognition)
Department of Computer Science

Room 10.136
Martensstr. 3
91058 Erlangen
Germany

Phone number: +49 9131 85-27775
Fax number: +49 9131 85-27270
Email: luis.rivera@fau.de
Website: https://lme.tf.fau.de/person/rivera/

Academic CV

Since 11/2020:
Ph.D. Student at Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg
09/2017 – 06/2020:
Master of Science in Medical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg
06/2015 – 06/2018:
Researcher at the Biomedical Computer Vision Group (BCV), Biomedical Engineering Department, Universidad de los Andes, Bogota-Colombia
01/2013 – 05/2017:
Bachelor in Biomedical Engineering, Universidad de los Andes, Bogota-Colombia

Projects

No projects found.

Publications

2020

Book Contributions

Maier J., Rivera Monroy L., Syben C., Jeon Y., Choi JH., Hall M., Levenston M., Gold G., Fahrig R., Maier A.:
Multi-Channel Volumetric Neural Network for Knee Cartilage Segmentation in Cone-Beam CT
In: Thomas Tolxdorff, Thomas M. Deserno, Heinz Handels, Andreas Maier, Klaus H. Maier-Hein, Christoph Palm (ed.): Bildverarbeitung für die Medizin 2020, Wiesbaden: Springer Vieweg, 2020, p. 67-72 (Informatik aktuell)
ISBN: 9783658292669
DOI: 10.1007/978-3-658-29267-6_14
BibTeX: Download

2018

Journal Articles

Winzeck S., Hakim A., Mckinley R., Pinto JAADSR., Alves V., Silva C., Pisov M., Krivov E., Belyaev M., Monteiro M., Oliveira A., Choi Y., Palk MC., Kwon Y., Lee H., Kim BJ., Won JH., Islam M., Ren H., Robben D., Suetens P., Gong E., Niu Y., Xu J., Pauly JM., Lucas C., Heinrich MP., Rivera LC., Castillo LS., Daza LA., Beers AL., Arbelaers P., Maier O., Chang K., Brown JM., Kapalthy-Cramer J., Zaharchuk G., Wiest R., Reyes M.:
ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI
In: Frontiers in Neurology 9 (2018), Article No.: 679
ISSN: 1664-2295
DOI: 10.3389/fneur.2018.00679
BibTeX: Download

Conference Contributions

Silvana Castillo L., Alexandra Daza L., Rivera LC., Arbelaez P.:
Brain Tumor segmentation and parsing on MRIs using multiresolution neural networks
3rd International Workshop on Brainlesion, BrainLes 2017 Held in Conjunction with Medical Image Computing for Computer Assisted Intervention , MICCAI 2017 (Quebec City, QC, September 14, 2017 - September 14, 2017)
In: Bjoern Menze, Alessandro Crimi, Hugo Kuijf, Mauricio Reyes, Spyridon Bakas (ed.): Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2018
DOI: 10.1007/978-3-319-75238-9_29
BibTeX: Download

2017

Conference Contributions

Silvana Castillo L., Alexandra Daza L., Rivera LC., Arbelaez P.:
Volumetric multimodality neural network for brain tumor segmentation
13th International Conference on Medical Information Processing and Analysis, SIPAIM 2017 (San Andres Island, October 5, 2017 - October 7, 2017)
In: Natasha Lepore, Jorge Brieva, Juan David Garcia, Eduardo Romero (ed.): Proceedings of SPIE - The International Society for Optical Engineering 2017
DOI: 10.1117/12.2285942
BibTeX: Download

Lectures

Lecture (VORL)

Medical Image Processing for Interventional Applications (online course)

mathematics for engineering; This lecture focuses on interventional procedures. It is recommended but not necessary to attend Medical Image Processing for Diagnostic Applications (MIPDA) before.
- 4 SWS; Expected participants: 150; ECTS studies (ECTS credits: 5), Lecture's language English
- Date:
  - Time and place on appointment
Medical Image Processing for Diagnostic Applications (VHB course)

Requirements: mathematics for engineering

Organization:
This is an online course of Virtuelle Hochschule Bayern (VHB).
Go to https://www.vhb.org to register to this course.
FAU students register for the written exam via meinCampus.
- 4 SWS; Expected participants: 150; ECTS studies (ECTS credits: 5), Lecture's language English
- Date:
  - Time and place on appointment

Student Thesis and Research Projects

Type	Title	Status
MA thesis	Multi-domain Stain Normalization for Digital Pathology (MELC Images)	open
MA thesis	Deep learning method for emotion recognition through the Fusion of body and context features	finished