Cookie Settings

We use cookies to optimize our website. These include cookies that are necessary for the operation of the site, as well as those that are only used for anonymous statistic. You can decide for yourself which categories you want to allow. Further information can be found in our data privacy protection .

Essential

These cookies are necessary to run the core functionalities of this website and cannot be disabled.

Name Webedition CMS
Purpose This cookie is required by the CMS (Content Management System) Webedition for the system to function correctly. Typically, this cookie is deleted when the browser is closed.
Name econda
Purpose Session cookie emos_jcsid for the web analysis software econda. This runs in the “anonymized measurement” mode. There is no personal reference. As soon as the user leaves the site, tracking is ended and all data in the browser are automatically deleted.
Statistics

These cookies help us understand how visitors interact with our website by collecting and analyzing information anonymously. Depending on the tool, one or more cookies are set by the provider.

Name econda
Purpose Statistics
External media

Content from external media platforms is blocked by default. If cookies from external media are accepted, access to this content no longer requires manual consent.

Name YouTube
Purpose Show YouTube content
Name Twitter
Purpose activate Twitter Feeds

Dr. Tobias Norajitra

Dr. Tobias Norajitra

Dr. Tobias Norajitra

Position:

Scientist

Phone:

+49(0) 6221/42-3550

Fax:

+49(0) 6221/42-2345

Building:

REZ

Room:

F.02.077

Tobias Norajitra is a Senior Scientist, Postdoc and Group Lead at the Division of Medical Image Computing (MIC) at the German Cancer Research Center (DKFZ). He holds a PhD in computer science from MIC/DKFZ and Karlsruhe Institute of Technology (KIT), after earning his Master's degree in computer science from KIT.

Projects:

  • Quality-controlled large scale image analyis in the German National Cohort
  • Computational analysis of subclinical comorbidities in clinical routine CT data
  • Shape and texture based quantification of COPD from MRI in the German National Cohort

Interests:

  • Machine Learning
  • Disease prediction and quantification
  • Image segmentation, shape modeling and Radiomics

to top
powered by webEdition CMS