Partner & Managing Director:
Dipl.-Ing. Frank Thilo Trautwein
04109 Leipzig, Germany
Tel. +49 341 656702-01
Tel. +1 646 878 9011 (US & Canada)
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70794 Filderstadt, Germany
Tel. +49 341 656702-10
Fax +49 341 656702-02
Leipzig, HRB 34218
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We research and develop methods for obtaining information from clinical image data. This information must be objective, reliable and, if possible, automatically extractable. This is the only way to reliably assess the healing process or the implant function and to achieve an evidence-based improvement in treatment methods.
The methods used come mainly from the areas of computer vision, artificial intelligence and big data. We are supported in the development of these procedures by the ESF and EU ERDF funds.
Project description: “Research into methods for the first exact, objective and fully automatic analysis of radiographic spine images”
Project period: 15 August 2017–14 August 2020
Implementation period: 15 August 2017–14 November 2020
Although radiologic evaluation is fundamental for the entire treatment spectrum of patients with back pain, radiologic analysis techniques for the exact quantification and evaluation of the complex anatomy and function of the spinal column have only been developed rudimentarily. For evidence-based diagnosis and treatment and as an essential contribution to clinical research, however, precise analytical methods are urgently needed. The aim of this project is to explore methods for a patient-friendly, automated analysis of radiographic image data, which leads to an exact and objective determination and visualization of clinically highly relevant parameters in all anatomical levels. The medium term goal of this research project is a medical software platform that can be integrated into everyday clinical practice and automatically allows the physician to perform a comprehensive functional and morphological characterization of the patient using standard radiographs. In the future, the results could be related to values of patients with a comparable diagnosis and the data of their treatment course, thus, for the first time, enabling evidence-based diagnosis and treatment course prognosis. The methods to be researched are also to be transferred to other clinical problem areas in the future.
This project is funded by the EFRE and the State of Saxony-Anhalt.