Optimising the illumination spectrum for enhancing tissue visualisation

Abstract

In operations, light reflected from biological tissue can be used for disease detection. In this paper, we used a visual entropy evaluation method to design the optimal illuminant to improve colour discriminability of biological tissue. The optimal spectral power distribution of the illuminant was obtained by maximising the visual entropy value of sample tissue based on the human visual system. In the experiment, multispectral imaging was used to measure the spectral reflectance of the tissue and colour clustering was conducted to extract its colour features. To verify the effectiveness of this method, simulated tissue images under illuminations with optimised spectral power distributions were compared with those under other light sources such as the standard illuminant D65 and white LED light sources. Results show that the sample under optimised illumination has a higher visual entropy value with better perceptual visibility.

Metrology and Measurement Systems

“…These parameters are based on the results of many years of research in terms of correct recognition of objects illuminated by various SPDs, thus some of them -also these associated with colour recognition -are frequently taken into account as the criteria for the spectral composition of multi-emitter sources [33]. In this kind of application however, an additional criterion usually means different SPD, which is also affected by an assumed amount of spectral components and for this reason we can observe a variety of possible technical solutions [34][35][36][37].…”

Improved and Robust Spectral Reflectance Estimation

“…The spectral reflectance of a surface is a unique property that is independent of the impinging illumination (Healey G 1991;Dana 2016), and is responsible, along with illumination's spectral power distribution (SPD), for the surface's (object's) color appearance. The spectral reflectance information is therefore useful for illuminating engineering applications (Durmus et al 2020), such as color tuning Durmus and Davis 2018), visual enhancement (Wang H et al 2018;Shen et al 2019), energy saving (Durmus and Davis 2015;Zhang JJ et al 2019), and computer vision application, such as surface/material recognition and characterization (Tominaga Shoji and Okajima 2000;Tu et al 2015), for image enhancement (Fu X et al 2015), for color constancy (Dixon and Shapiro 2017) and for geometry (shape) estimation from shading (Oxholm and Nishino 2016). Moreover, it is also useful in realistic material reproduction under a variety of illumination conditions in computer graphics (Filip et al 2017) and in relighting (Xing et al 2010), where multispectral reflectance approaches (Shrestha et al 2011;Khan et al 2013) can hardly meet the requirements.…”

Tunable LED illumination for biological tissue imaging

“…One of the innovative tools developed for biological tissue imaging is a tunable broadband LED illuminator (TBLEDI) [4,5]. This advanced technology makes it possible to obtain highquality images, which is crucial for accurately diagnosing various diseases and conditions [6][7][8].…”