Dr Martin Urschler


I received the MSc in Computer Science and Electrical Engineering (Telematik) as well as the PhD in Computer Science from Graz University of Technology. After my PhD studies, which focused on nonlinear registration of computed tomography images, I worked for two years as a post doc in Graz on biometric image analysis. Later, I joined the Ludwig Boltzmann Institute for Clinical Forensic Imaging (LBI CFI) in Graz, while remaining an affiliated lecturer for Medical Image Analysis at the Institute of Computer Graphics and Vision at Graz University of Technology. In 2015 I became a key researcher and principal investigator at the LBI CFI, before I moved to the University of Auckland's Department of Computer Science in 2019.

Research | Current

My research interests are in medical image analysis, computer vision and machine learning techniques applied to medical and forensic applications. More information can be found on my UoA personal page.

Areas of expertise

medical image analysis

medical computer vision

biometric image analysis

forensic imaging

machine learning in medical/forensic applications

Selected publications and creative works (Research Outputs)

  • Neumayer, B., Lesch, A., Thaler, F., Widek, T., Tschauner, S., De Tobel, J., ... van Wijk, M. (2019). The four-minute approach revisited: accelerating MRI-based multi-factorial age estimation. International journal of legal medicine10.1007/s00414-019-02231-w
  • Payer, C., Štern D, Feiner, M., Bischof, H., & Urschler, M. (2019). Segmenting and tracking cell instances with cosine embeddings and recurrent hourglass networks. Medical image analysis, 57, 106-119. 10.1016/j.media.2019.06.015
  • Payer, C., Štern D, Bischof, H., & Urschler, M. (2019). Integrating spatial configuration into heatmap regression based CNNs for landmark localization. Medical image analysis, 54, 207-219. 10.1016/j.media.2019.03.007
  • Stern, D., Payer, C., Giuliani, N., & Urschler, M. (2018). Automatic Age Estimation and Majority Age Classification from Multi-Factorial MRI Data. IEEE journal of biomedical and health informatics, 23 (4), 1392-1403. 10.1109/jbhi.2018.2869606
  • Payer, C., Stern, D., Bischof, H., & Urschler, M. (2018). Multi-label Whole Heart Segmentation Using CNNs and Anatomical Label Configurations. Paper presented at 8th International Workshop on Statistical Atlases and Computational Models of the Heart (STACOM), Quebec, CANADA. 10 September - 14 September 2017. STATISTICAL ATLASES AND COMPUTATIONAL MODELS OF THE HEART: ACDC AND MMWHS CHALLENGES. (pp. 9). 10.1007/978-3-319-75541-0_20
  • Urschler, M., Ebner, T., & Štern D (2018). Integrating geometric configuration and appearance information into a unified framework for anatomical landmark localization. Medical image analysis, 43, 23-36. 10.1016/j.media.2017.09.003
  • Kainz, P., Pfeiffer, M., & Urschler, M. (2017). Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization. PeerJ, 510.7717/peerj.3874
  • Payer, C., Pienn, M., Bálint Z, Shekhovtsov, A., Talakic, E., Nagy, E., ... Urschler, M. (2016). Automated integer programming based separation of arteries and veins from thoracic CT images. Medical image analysis, 34, 109-122. 10.1016/j.media.2016.05.002


Contact details

Primary office location

SCIENCE CENTRE 303 - Bldg 303
Level 4, Room 421
New Zealand

Web links