Feature detection in biological tissues using multi-band and narrow-band imaging

  • Yuki Tamura
  • Tomohiro Mashita
  • Yoshihiro Kuroda
  • Kiyoshi Kiyokawa
  • Haruo Takemura
Original Article



In the past decade, augmented reality systems have been expected to support surgical operations by making it possible to view invisible objects that are inside or occluded by the skull, hands, or organs. However, the properties of biological tissues that are non-rigid and featureless require a large number of distributed features to track the movement of tissues in detail.


With the goal of increasing the number of feature points in organ tracking, we propose a feature detection using multi-band and narrow-band imaging and a new band selection method. The depth of light penetration into an object depends on the wavelength of light based on optical characteristics. We applied typical feature detectors to detect feature points using three selected bands in a human hand. To consider surgical situations, we applied our method to a chicken liver with a variety of light conditions.


Our experimental results revealed that the image of each band exhibited a different distribution of feature points. In addition, the total number of feature points determined by the proposed method exceeded that of the R, G, and B images obtained using a normal camera. The results using a chicken liver with various light sources and intensities also show different distributions with each selected band.


We have proposed a feature detection method using multi-band and narrow-band imaging and a band selection method. The results of our experiments confirmed that the proposed method increased the number of distributed feature points. The proposed method was also effective for different light conditions.


Multi-band imaging Narrow-band imaging Biological tissues Feature detection Augmented reality 


Compliance with ethical standards

Conflicts of interest

We have no conflicts of interest relationship with any companies or commercial organizations based on the definition of the Japanese Society of Medical and Biological Engineering.


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Copyright information

© CARS 2016

Authors and Affiliations

  • Yuki Tamura
    • 1
  • Tomohiro Mashita
    • 1
    • 2
  • Yoshihiro Kuroda
    • 3
  • Kiyoshi Kiyokawa
    • 1
    • 2
  • Haruo Takemura
    • 1
    • 2
  1. 1.Graduate School of Information Science and TechnologyOsaka UniversitySuita CityJapan
  2. 2.Cybermedia CenterOsaka UniversityToyonaka CityJapan
  3. 3.Graduate School of Engineering ScienceOsaka UniversityToyonaka CityJapan

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