DoctorEye: A Clinically Driven Multifunctional Platform, for Accurate Processing of Tumors in Medical Images

Emmanouil Skounakis*, 1, 2, Christina Farmaki1, Vangelis Sakkalis1, Alexandros Roniotis1, 3, Konstantinos Banitsas2, Norbert Graf4, Konstantinos Marias1
1 Foundation for Research and Technology Hellas (FORTH) - Institute of Computer Science - Heraklion, Crete, Greece
2 Department of Electronic & Computer Engineering, Brunel University, West London, UK
3 Department of Electronic and Computer Engineering, Technical University of Crete, Chania, Crete, Greece
4 University Hospital of the Saarland, Homburg, Germany

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© Skounakis et al.; Licensee Bentham Open.

open-access license: This is an open access article licensed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

* Address correspondence to this author at the Institute of Computer Science at FORTH, Vassilika Vouton, GR-70013 Heraklion, Crete, Greece; Tel:+30 2810 391340; Fax: +30 2810 391428; E-mail:


This paper presents a novel, open access interactive platform for 3D medical image analysis, simulation and visualization, focusing in oncology images. The platform was developed through constant interaction and feedback from expert clinicians integrating a thorough analysis of their requirements while having an ultimate goal of assisting in accurately delineating tumors. It allows clinicians not only to work with a large number of 3D tomographic datasets but also to efficiently annotate multiple regions of interest in the same session. Manual and semi-automatic segmentation techniques combined with integrated correction tools assist in the quick and refined delineation of tumors while different users can add different components related to oncology such as tumor growth and simulation algorithms for improving therapy planning. The platform has been tested by different users and over large number of heterogeneous tomographic datasets to ensure stability, usability, extensibility and robustness with promising results.


The platform, a manual and tutorial videos are available at:

It is free to use under the GNU General Public License.

Keywords: Medical imaging, interactive segmentation, image analysis, virtualization of the human physiology, computer aided diagnosis, decision support systems.