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Dr. Christian Martin




About

  • since 2020: Coordination of Life Science & Medicine projects in Transfer & Service at ScaDS.AI
  • since 2019: Research Associate at ScaDS.AI (Center for Scalable Data Analytics and Artificial Intelligence) Dresden/Leipzig
  • 2008 - 2019: Software Developer and Research Associate at Loeser/Meierhofer Medizintechnik GmbH
  • 2003 - 2008: Research Associate at Biodata Mining Group, University of Bielefeld
  • Graduation: Dr.-Ing., University of Bielefeld, 2009
  • Diploma in Computer Science, University of Bielefeld, 2003

Contact

  • +49 341 97 39306
  • christian.martin [at] informatik.uni-leipzig.de
  • ScaDS.AI (Center for Scalable Data Analytics and Artificial Intelligence) Dresden/Leipzig
  • Humboldtstrasse 25, 3.OG
  • 04105 Leipzig

Research Interests

  • Machine Learning
  • Statistical Learning
  • Life Science & Medicine
  • Personalized Medicine
  • Biomedical Data Analysis
  • Deep Learning
  • Image Processing
  • Radiomics

Projects

  • GRAMMY (ERA PerMed): InteGRAtive analysis of tuMor, Microenvironment, immunitY and patient expectation for personalized response prediction in Gastric Cancer
  • MIRACLE (ERA PerMed): A Machine learning approach to Identify patients with Resected non-small-cell lung cAnCer with high risk of reLapsE
  • SaxoCell
  • Radiomics
    • Classification of cancer types
    • Rupture risk prediction of aneurysms
    • Image Prediction

Tools

  • Predict rupture risk of intracranial aneurysm: Webtool

Talks

  • Personalized Medicine and Cancer Research at ScaDS.AI. Innovationsworkshop Künstliche Intelligenz in der Krebsforschung und -behandlung, 2022-07

Supervision of Thesis/Students

  • Running Thesis
    • Marlene Mertens (MA): Klassifikation von Cervix-Karzinomen in MRT-Bildern
    • Mohammad Issa (MA): Automatische Detektion und Segmentierung von Fahrspuren im Automotive Bereich (Kooperation mit ASAP ENGINEERING GmbH)
    • Jonathan Huthmann (MA): Vorhersage der Kontrastmittelanreicherung in 3D-Mamma MRT-Aufnahmen durch Einsatz von Deep Learning
  • Finished Thesis
    • 2022, Lucas Lange (MA): Privacy-Preserving Detection of COVID-19 in X-Ray Images (joint supervision with Maja Schneider)
    • 2021, Stefan Berger (MA): Feature Selection Methods to Predict Wafer Thickness in Chip Manufacturing (cooperation with Global Foundries)
    • 2021, Georg Walther (BA): Automatische Aneurysma-Detektion und Rupturvorhersage
  • Students (WHK)
    • 2020-2022, Marlene Mertens: Klassifikation on Tumor-Subtypen und Survival Analysis bei Magenkrebs (Projekt GRAMMY)
    • 2020-2022, Georg Walther: Machine Learning for Rupture Risk Prediction of Intracranial Aneurysms
    • 2021, Leo Seeger: Segmentierung von Mamma-MRT-Bildern mit Unsupervised Deep Learning
    • 2021, Emre Arkan: Erprobung von Treatment Response Assessment Maps (TRAMs) auf MRT-Bildern von Hirntumoren
    • 2020, Jan Beckert und Emre Arkan: Entwicklung eines Covid-19-Demonstrators zur Klassifikation von Röntgenbildern
  • Besondere Lernleistung (BeLL)
    • 2021/2022, John Petersen: Klassifizierung von Magnetresonanztomographie-Bildern mit konvolutionalen neuronalen Netzen [pdf]

Publications

PDF
further information
Google Scholar
publication iconWalther, Georg; Martin, Christian; Haase, Amelie; Nestler, Ulf; Schob, Stefan
Machine Learning for Rupture Risk Prediction of Intracranial Aneurysms: Challenging the PHASES Score
Symmetry 2022, 14(5), 943, Special Issue “Neuroscience and Molecular Sciences”
2022-05-05