Visual Healthcare Computing

The research area “Visual Healthcare Computing” describes the application of computer  vision, deep learning and visualization algorithms to the field of digital healthcare.
Examples are applications along a patient’s healthcare pathway, starting  from image based diagnostics (e.g. based on endoscopy or digital pathology), endoscopy-based image enhancement for orientation and navigation (using e.g. 2D/3D panoramic imaging), computer assisted radiomics (in the field of mammography), contactless monitoring of vital signs (e.g. pulse and breathing) as well as interactive immersive training and planning systems for surgical interventions.

Selected Publications:

• Klare P., Sander C., Prinzen M., Haller M., Nowack S., Abdelhafez M., Poszler A., Brown H., Wilhelm D., Schmidt RM., von Delius S., Wittenberg T.:
  Automated polyp detection in the colorectum: a prospective study (with videos)
  In: Gastrointestinal Endoscopy 89 (2019), p. 576-582.e1
  ISSN: 0016-5107
  DOI: 10.1016/j.gie.2018.09.042
  URL: https://www.ncbi.nlm.nih.gov/pubmed/30342029
  BibTeX: Download
• Kriegmayr M., Bergen T., Ritter M., Mandel P., Michel M., Wittenberg T., Bolenz C.:
  Digital Mapping of the Urinary Bladder: Potential for Standardized Cystoscopy Reports.
  In: Urology 104 (2017), p. 235-241
  ISSN: 0090-4295
  DOI: 10.1016/j.urology.2017.02.019
  URL: https://www.ncbi.nlm.nih.gov/pubmed/28214573
  BibTeX: Download
• Haeberle L., Hack C., Heusinger K., Wagner F., Jud S., Uder M., Beckmann M., Schulz-Wendtland R., Wittenberg T., Fasching P.:
  Using automated texture features to determine the probability for masking of a tumor on mammography, but not ultrasound
  In: European Journal of Medical Research 22 (2017)
  ISSN: 0949-2321
  DOI: 10.1186/s40001-017-0270-0
  URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5577694/
  BibTeX: Download
• Aichinger W., Krappe S., Enis AC., Cetin-Atalay R., Üner A., Benz M., Wittenberg T., Stamminger M., Münzenmayer C.:
  Automated cancer stem cell recognition in H and E stained tissue using convolutional neural networks and color deconvolution
  SPIE Medical Imaging 2017 (Orlando, Florida, USA)
  In: Proceedings Volume 10140 Medical Imaging 2017:Digital Pathology 2017
  DOI: 10.1117/12.2254036
  BibTeX: Download
• Krappe S., Benz M., Gryanik A., Tannich E., Wegner C., Stamminger M., Wittenberg T., Münzenmayer C.:
  Automated plasmodia recognition in microscopic images for diagnosis of malaria using convolutional neural networks
  Medical Imaging: Digital Pathology 2017
  DOI: 10.1117/12.2249845
  BibTeX: Download