Narrow-band imaging for the computer assisted diagnosis in patients with Barrett's esophagus

Andreas Kage; Martin Raithel; Steffen Zopf; Thomas Wittenberg; Christian Münzenmayer

doi:10.1117/12.812257

27 February 2009 Narrow-band imaging for the computer assisted diagnosis in patients with Barrett's esophagus

Andreas Kage, Martin Raithel, Steffen Zopf, Thomas Wittenberg, Christian Münzenmayer

Proceedings Volume 7260, Medical Imaging 2009: Computer-Aided Diagnosis; 72603S (2009) https://doi.org/10.1117/12.812257
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States

Abstract

Cancer of the esophagus has the worst prediction of all known cancers in Germany. The early detection of suspicious changes in the esophagus allows therapies that can prevent the cancer. Barrett's esophagus is a premalignant change of the esophagus that is a strong indication for cancer. Therefore there is a big interest to detect Barrett's esophagus as early as possible. The standard examination is done with a videoscope where the physician checks the esophagus for suspicious regions. Once a suspicious region is found, the physician takes a biopsy of that region to get a histological result of it. Besides the traditional white light for the illumination there is a new technology: the so called narrow-band Imaging (NBI). This technology uses a smaller spectrum of the visible light to highlight the scene captured by the videoscope. Medical studies indicate that the use of NBI instead of white light can increase the rate of correct diagnoses of a physician. In the future, Computer-Assisted Diagnosis (CAD) which is well known in the area of mammography might be used to support the physician in the diagnosis of different lesions in the esophagus. A knowledge-based system which uses a database is a possible solution for this task. For our work we have collected NBI images containing 326 Regions of Interest (ROI) of three typical classes: epithelium, cardia mucosa and Barrett's esophagus. We then used standard texture analysis features like those proposed by Haralick, Chen, Gabor and Unser to extract features from every ROI. The performance of the classification was evaluated with a classifier using the leaving-one-out sampling. The best result that was achieved is an accuracy of 92% for all classes and an accuracy of 76% for Barrett's esophagus. These results show that the NBI technology can provide a good diagnosis support when used in a CAD system.

Citation Download Citation

Andreas Kage, Martin Raithel, Steffen Zopf, Thomas Wittenberg, and Christian Münzenmayer "Narrow-band imaging for the computer assisted diagnosis in patients with Barrett's esophagus", Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72603S (27 February 2009); https://doi.org/10.1117/12.812257

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