Academic Career and Research Areas
Prof. Wachinger conducts research on novel AI algorithms for the analysis of medical images and their translation into clinical practice. He develops multimodal models for disease prediction and uses big data to train complex neural networks. Currently, he is focusing on the following challenges: (i) transparency of AI, (ii) integration of heterogeneous data, and (iii) generalization, bias, and fairness.
Prof. Wachinger studied computer science at TUM and ENST Paris. He holds an Honours Degree in Technology Management from CDTM. In 2011, he received his PhD in medical image analysis from TUM. As a post-doc, he was at the Massachusetts Institute of Technology in Cambridge and Harvard Medical School in Boston, USA. Subsequently, he took over an interims-professorship at the Ludwig-Maximilians-University of Munich. In 2021, he was appointed to the professorship for AI in radiology at TUM.
- Junior research group from Zentrum Digitalisierung Bayern (2017)
- Prize for our results in the CADDementia Challenge (2014)
- Gesellschaft für Informatik Ausgezeichnete Informatikdissertationen (2011)
- Feodor Lynen Research Fellowship from the Alexander von Humboldt Foundation (2011)
- Siemens Excellence Award (2007)
Key Publications (all publications)
Wachinger C, Rieckmann A, Pölsterl S, “Detect and correct bias in multi-site neuroimaging datasets”. Medical Image Analysis. 2021.Abstract
Roy AG, Navab N, Wachinger C. “Recalibrating fully convolutional networks with spatial and channel ‘squeeze and excitation’ blocks”. IEEE transactions on medical imaging. 2018. 38(2):540-9.Abstract
Wachinger C, Salat DH, Weiner M, Reuter M, “Whole-brain analysis reveals increased neuroanatomical asymmetries in dementia for hippocampus and amygdala”. Brain. 2016.Abstract
Wachinger C, Golland P, Kremen W, Fischl B, Reuter M, Alzheimer's Disease Neuroimaging Initiative. BrainPrint: A discriminative characterization of brain morphology. NeuroImage. 2015. 109:232-48.Abstract
Wachinger C, Navab N. “Simultaneous registration of multiple images: Similarity metrics and efficient optimization”. IEEE transactions on pattern analysis and machine intelligence. 2012. 35(5):1221-33.Abstract