Hyperspectral imaging is one of the most promising techniques for intraoperative tissue characterisation. Snapshot mosaic cameras, which can capture hyperspectral data in a single exposure, have the potential to make a real-time hyperspectral imaging system for surgical decision-making possible. However, optimal exploitation of the captured data requires solving an ill-posed demosaicking problem and applying additional spectral corrections. In this work, we propose a supervised learning-based image demosaicking algorithm for snapshot hyperspectral images. Due to the lack of publicly available medical images acquired with snapshot mosaic cameras, a synthetic image generation approach is proposed to simulate snapshot images from existing medical image datasets captured by high-resolution, but slow, hyperspectral imaging devices. Image reconstruction is achieved using convolutional neural networks for hyperspectral image super-resolution, followed by spectral correction using a sensor-specific calibration matrix. The results are evaluated both quantitatively and qualitatively, showing clear improvements in image quality compared to a baseline demosaicking method using linear interpolation. Moreover, the fast processing time of 45 ms of our algorithm to obtain super-resolved RGB or oxygenation saturation maps per image for a state-of-the-art snapshot mosaic camera demonstrates the potential for its seamless integration into real-time surgical hyperspectral imaging applications.

The fraction of exhaled nitric oxide (FENO) is an important biomarker for the diagnosis and management of asthma and other pulmonary diseases associated with airway inflammation. In this study we report on a novel method for accurate, highly time-resolved, real time detection of FENO at the mouth. The experimental arrangement is based on a combination of optical sensors for the determination of the temporal profile of exhaled NO and CO2 concentrations. Breath CO2 and exhalation flow are measured at the mouth using diode laser absorption spectroscopy (at 2 μm) and differential pressure sensing, respectively. NO is determined in a sidestream configuration using a quantum cascade laser based, cavity-enhanced absorption cell (at 5.2 μm) which simultaneously measures sidestream CO2. The at-mouth and sidestream CO2 measurements are used to enable the deconvolution of the sidestream NO measurement back to the at-mouth location. All measurements have a time resolution of 0.1 s, limited by the requirement of a reasonable limit of detection for the NO measurement, which on this timescale is 4.7 ppb (2 σ). Using this methodology, NO expirograms (FENOgrams) were measured and compared for eight healthy volunteers. The FENOgrams appear to differ qualitatively between individuals and the hope is that the dynamic information encoded in these FENOgrams will provide valuable additional insight into the location of the inflammation in the airways and potentially predict a response to therapy. A validation of the measurements at low-time resolution is provided by checking that results from previous studies that used a two-compartment model of NO production can be reproduced using our technology.

Hyperspectral imaging shows promise for surgical applications to noninvasively provide spatially resolved, spectral information. For calibration purposes, a white reference image of a highly reflective Lambertian surface should be obtained under the same imaging conditions. Standard white references are not sterilizable and so are unsuitable for surgical environments. We demonstrate the necessity for in situ white references and address this by proposing a novel, sterile, synthetic reference construction algorithm.Approach: The use of references obtained at different distances and lighting conditions to the subject were examined. Spectral and color reconstructions were compared with standard measurements qualitatively and quantitatively, using ΔE and normalized RMSE, respectively. The algorithm forms a composite image from a video of a standard sterile ruler, whose imperfect reflectivity is compensated for. The reference is modeled as the product of independent spatial and spectral components, and a scalar factor accounting for gain, exposure, and light intensity. Evaluation of synthetic references against ideal but non-sterile references is performed using the same metrics alongside pixel-by-pixel errors. Finally, intraoperative integration is assessed though cadaveric experiments.Results: Improper white balancing leads to increases in all quantitative and qualitative errors. Synthetic references achieve median pixel-by-pixel errors lower than 6.5% and produce similar reconstructions and errors to an ideal reference. The algorithm integrated well into surgical workflow, achieving median pixel-by-pixel errors of 4.77% while maintaining good spectral and color reconstruction. Conclusions:We demonstrate the importance of in situ white referencing and present a novel synthetic referencing algorithm. This algorithm is suitable for surgery while maintaining the quality of classical data reconstruction.

Optical imaging modalities are non-ionizing methods with significant potential for noninvasive, portable, and cost-effective medical diagnostics and treatments. The design of critical parameters of an optical imaging system depends on a thorough understanding of optical properties of the biological tissue within the purposed application. Integrating sphere technique combined with inverse adding doubling algorithm has been widely used for determination of biological tissue ex vivo. It has been studied for tissues typically with a large sample size (approx. 20 x 20 mm) and over a spectral range of 400 nm to 1100 nm. The aim of this study is to develop a methodology for calculating optical absorption µ a and reduced scattering µ ′ s of small size (approx. 6 x 8 mm) biological tissues from reflectance and transmittance measurements at a wide spectral range of 400 to 1800 nm. We developed a small sample adaptor kit to allow integrating sphere measurements of samples with small sizes using a commercial device. Dual beam single integrating sphere technique was used to the total transmittance (T total ) and total reflectance (R total ) measurements of samples, and inverse adding doubling (IAD) was used to convert the measurements T total and R total to optical properties. We proposed a two-tier IAD algorithm to mitigate the profound cross-talk effect in reduced scattering using IAD. We evaluated the two-tier IAD with both simulated data by Monte Carlo Simulation and data obtained from phantom experiments. We also investigated the accuracy the proposed work flow of using small sample kit and condensed incident light beam. We found that the small sample measurements despite with condense beam size led to overestimated absorption coefficient across the whole wavelength range while the spectrum shape well preserved. Our proposed method of a two-tier IAD and small sample kit could be a useful and reliable tool to characterise optical properties of biological tissue ex vivo particularly when only small size samples are available.