Hyperspectral interventional imaging for enhanced tissue visualization and discrimination combining band selection methods

Int J Comput Assist Radiol Surg. 2016 Dec;11(12):2185-2197. doi: 10.1007/s11548-016-1449-5. Epub 2016 Jul 4.

Abstract

Purpose: Hyperspectral imaging is an emerging technology recently introduced in medical applications inasmuch as it provides a powerful tool for noninvasive tissue characterization. In this context, a new system was designed to be easily integrated in the operating room in order to detect anatomical tissues hardly noticed by the surgeon's naked eye.

Method: Our LCTF-based spectral imaging system is operative over visible, near- and middle-infrared spectral ranges (400-1700 nm). It is dedicated to enhance critical biological tissues such as the ureter and the facial nerve. We aim to find the best three relevant bands to create a RGB image to display during the intervention with maximal contrast between the target tissue and its surroundings. A comparative study is carried out between band selection methods and band transformation methods. Combined band selection methods are proposed. All methods are compared using different evaluation criteria.

Results: Experimental results show that the proposed combined band selection methods provide the best performance with rich information, high tissue separability and short computational time. These methods yield a significant discrimination between biological tissues.

Conclusion: We developed a hyperspectral imaging system in order to enhance some biological tissue visualization. The proposed methods provided an acceptable trade-off between the evaluation criteria especially in SWIR spectral band that outperforms the naked eye's capacities.

Keywords: Dimensionality reduction; Hyperspectral imaging; LCTF; SWIR; Tissue discrimination; Visualization enhancement.

Publication types

  • Review

MeSH terms

  • Algorithms
  • Facial Nerve / diagnostic imaging*
  • Facial Nerve / surgery
  • Humans
  • Image Processing, Computer-Assisted* / methods
  • Narrow Band Imaging*
  • Pattern Recognition, Automated
  • Ureter / diagnostic imaging*
  • Ureter / surgery