Vascular pattern detection and recognition in endoscopic imaging of the vocal folds

Axel Boese 1 , Alfredo Illanes 2 , Sathish Balakrishnan 2 , Nikolaos Davaris 3 , Christoph Arens 3  and Michael Friebe 2
  • 1 Institute of medical technology, INKA, Otto-von-Guericke University,, Magdeburg, Germany
  • 2 Institute of medical technology, INKA, Otto-von-Guericke University,, Magdeburg, Germany
  • 3 Department of Otorhinolaryngology, Head & Neck Surgery, University Hospitals Magdeburg, Otto-von-Guericke-University,, Magdeburg, Germany

Abstract

At present transoral laryngeal interventions are mainly observed and controlled by an external two dimensional direct microscopic view. This modality provides an overall view on the surgery situs in a straight line of sight. For treatment planning and appropriate documentation, an endoscopic inspection is mandatory prior to surgery. Nowadays a detailed endoscopic work-up of laryngeal lesions can be performed by contact endoscopy in combination with structure enhancement like Narrow Band Imaging. High resolution and magnification of up to 150 times provide detailed visualization of vascular structures and pathological changes of the tissue surface. In these procedures it is difficult however to localize the evaluated areas on large scale scenes like the microscopic view used for surgery. To provide a fast and easy image matching an automated vessel pattern recognition and allocation is presented. Endoscopic images depicting representative vessel structures of the vocal folds are selected out of contact endoscopy video scenes. These images are pre-processed for background homogenization. A Frangi Vessel Segmentation filter and morphological operations are used to extract the vessel structure and match it to the microscopic image. Using this method 4 detailed contact endoscopy images could be allocated in different scenes of the microscope video. This method can be used to simplify treatment planning and to prepare image data for documentation.

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Current Directions in Biomedical Engineering is an open access journal and closely related to the journal Biomedical Engineering - Biomedizinische Technik. CDBME is a forum for the exchange of knowledge in the fields of biomedical engineering, medical information technology and biotechnology/bioengineering for medicine and addresses engineers, natural scientists, and clinicians working in research, industry, or clinical practice.

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