Personen
Portrait von Lalith Sharan, M.Sc.
Lalith Sharan, M.Sc.

Wiss. Mitarbeiter (Klinik für Herzchirurgie)
Wiss. Mitarbeiter (AG Artificial Intelligence in Cardiovascular Medicine)
Wiss. Mitarbeiter (Klinik für Kardiologie, Angiologie, Pneumologie)

Schwerpunkt

Quantitative endoscopic image analysis for mitral valve repair


06221 56-8110

AG Künstliche Intelligenz in der Kardiovaskulären Medizin

Ärztlicher / Beruflicher Werdegang

seit November 2019

Wissenschaftlicher Mitarbeiter, AG Artificial Intelligence in Cardiovascular Medicine, Universitätsklinik Heidelberg, Germany

seit November 2019

Scientist, Informatics for Life, Heidelberg, Germany
(www.informatics4life.org)

April 2019 – September 2019

Masterand, Forschungsprojekt "Computer-based Quantification of Reconstructive Mitral Valve Surgery", Hochschule Mannheim und Universitätsklinik Heidelberg, Germany

Oktober 2018 – März 2019

Wissenschaftliche Hilfskraft, Forschungsprojekt "Computer-based Quantification of Reconstructive Mitral Valve Surgery", Hochschule Mannheim und Universitätsklinik Heidelberg, Germany

Januar 2018 – September 2018

Wissenschaftliche Hilfskraft, Computer Assisted Surgeries (CAS) group, Otto von Guericke Universitaet, Magdeburg, Germany

Januar 2014 – Mai 2014

Bachelorand, Forschungsprojekt "Cognitive state assessment using EEG signals", Institute of Nuclear Medicine and Allied Sciences, New Delhi, India

Mai 2013 – August 2013

Praktikant, Siemens Innovation Think Tank (ITT), Siemens Healthcare Pvt. Ltd. (Now Siemens Healthineers), Goa, India

Wissenschaftlicher Werdegang

seit November 2019

Ph.D. student, AG Artificial Intelligence in Cardiovascular Medicine, Heidelberg University Hospital, Heidelberg, Germany
Focus: Quantitative endoscopic image analysis for mitral valve surgery

April 2017 – Oktober 2019

Master of Science in Medical Systems Engineering,
Otto von Guericke Universitaet, Magdeburg, Germany
Focus: Computer assisted surgeries, computer vision, deep learning

Juli 2010 – Mai 2014

Bachelor of Engineering in Biomedical Engineering,
Manipal Institute of Technology, Karnataka, India
Focus: Medical image & signal processing, Pattern recognition

Publikationen

Preetha, C.J., Wehrtmann, F.S., Sharan, L., Fan, C., Kloss, J., Müller-Stich, B.P., Nickel, F., Engelhardt, S., Towards augmented reality-based suturing in monocular laparoscopic training. Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 113150X (16 March 2020); (https://doi.org/10.1117/12.2550830)

Engelhardt, S., Sharan, L., Karck, M., De Simone, R., Wolf, I., Cross-Domain Conditional Generative Adversarial Networks for Stereoscopic Hyperrealism in Surgical Training. In: Shen D. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2019. MICCAI 2019. Lecture Notes in Computer Science, vol 11768. Springer, Cham, pp 155-163,  (doi.org/10.1007/978-3-030-32254-0_18)