Speckle Reduction with Attenuation Compensation for Skin OCT Images Enhancement

The enhancement of skin image in optical coherence tomography (OCT) imaging can help dermatologists to investigate tissue layers more accurately, hence the more efficient diagnosis. In this paper, we propose an image enhancement technique including speckle reduction, attenuation compensation and cleaning to improve the quality of OCT skin images. A weighted median filter is designed to reduce the level of speckle noise while preserving the contrast. A novel border detection technique is designed to outline the main skin layers, stratum corneum, epidermis and dermis. A model of the light attenuation is then used to estimate the absorption coefficient of epidermis and dermis layers and compensate the brightness of the structures at deeper levels. The undesired part of the image is removed using a simple cleaning algorithm. The performance of the algorithm has been evaluated visually and numerically using the commonly used no-reference quality metrics. The results shows an improvement in the quality of the images. Keywords: Optical coherence tomography (OCT), Skin, Image enhancement, Speckle reduction, Attenuation compensation

Motion Artifact Reduction in Breast Dynamic Infrared Imaging

Dynamic infrared imaging is a promising technique in breast oncology. In this study a QWIP infrared camera is used to acquire a sequence of consecutive thermal images of the patient's breast for 10 s. Information on the local blood perfusion is obtained from the spectral analysis of the time series at each image pixel. Due to respiratory and motion artifacts, the direct comparison of the temperature values that a pixel assumes along the sequence becomes difficult. In fact, the small temperature changes due to blood perfusion, of the order of 10-50 mK, which constitute the signal of interest in the time domain, are superimposed onto large temperature fluctuations due to the subject's motion, which represent noise. To improve the time series signal-to-noise ratio, and, as a consequence, enhance the specificity and sensitivity of the dynamic infrared examination, it is important to realign the thermal images of the acquisition sequence thus reducing motion artifacts. In a previous study we demonstrated that a registration algorithm based on fiducial points is suitable to both clinical applications and research, when associated with a proper set of skin markers. In this paper, we quantitatively evaluate the performance of different marker sets by means of a model that allows for estimating the signal-to-noise ratio increment due to registration, and we conclude that a 12-marker set is a good compromise between motion artifact reduction and the time required to prepare the patien

Photonic integrated Mach-Zehnder interferometer with an on-chip reference arm for optical coherence tomography

Optical coherence tomography (OCT) is a noninvasive, three-dimensional imaging modality with several medical and industrial applications. Integrated photonics has the potential to enable mass production of OCT devices to significantly reduce size and cost, which can increase its use in established fields as well as enable new applications. Using silicon nitride (Si(3)N(4)) and silicon dioxide (SiO(2)) waveguides, we fabricated an integrated interferometer for spectrometer-based OCT. The integrated photonic circuit consists of four splitters and a 190 mm long reference arm with a foot-print of only 10 × 33 mm(2). It is used as the core of a spectral domain OCT system consisting of a superluminescent diode centered at 1320 nm with 100 nm bandwidth, a spectrometer with 1024 channels, and an x-y scanner. The sensitivity of the system was measured at 0.25 mm depth to be 65 dB with 0.1 mW on the sample. Using the system, we imaged human skin in vivo. With further optimization in design and fabrication technology, Si(3)N(4)/SiO(2) waveguides have a potential to serve as a platform for passive photonic integrated circuits for OCT

Quantifying Cross-scatter Contamination in Biplane Fluoroscopy Motion Analysis Systems

Biplane fluoroscopy is used for dynamic in vivo three-dimensional motion analysis of various joints of the body. Cross-scatter between the two fluoroscopy systems may limit tracking accuracy. This study measured the magnitude and effects of cross-scatter in biplane fluoroscopic images. Four cylindrical phantoms of 4-, 6-, 8-, and 10-in. diameter were imaged at varying kVp levels to determine the cross-scatter fraction and contrast-to-noise ratio (CNR). Monte Carlo simulations quantified the effect of the gantry angle on the cross-scatter fraction. A cadaver foot with implanted beads was also imaged. The effect of cross-scatter on marker-based tracking accuracy was investigated. Results demonstrated that the cross-scatter fraction varied from 0.15 for the 4-in. cylinder to 0.89 for the 10-in. cylinder when averaged across kVp. The average change in CNR due to cross-scatter ranged from 5% to 36% CNR decreases for the 4- and 10-in. cylinders, respectively. In simulations, the cross-scatter fraction increased with the gantry angle for the 8- and 10-in. cylinders. Cross-scatter significantly increased static-tracking error by 15%, 25%, and 38% for the 6-, 8-, and 10-in. phantoms, respectively, with no significant effect for the foot specimen. The results demonstrated submillimeter marker-based tracking for a range of phantom sizes, despite cross-scatter degradation

Developing non-destructive techniques to predict 'Hayward' kiwifruit storability : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Food Technology at Massey University, Palmerston North, New Zealand

A significant portion of New Zealand’s kiwifruit production is held as stock in local coolstores for extended periods of time before being exported. Many pre-harvest factors contribute to variation in fruit quality at harvest and during coolstorage, and results in the difficulty in segregating fruit for their storage outcomes. The objective of this work was to develop non-destructive techniques utilised at harvest to predict storability of individual or batches of ‘Hayward’ kiwifruit based on (near) skin properties. Segregation of fruit with low storage potential at harvest could enable that fruit to be sold earlier in the season reducing total fruit loss and improving profitability later in the season. The potential for optical coherence tomography (OCT) to detect near surface cellular structural differences in kiwifruit as a result of preharvest factors was demonstrated through quantitative image analysis of 3D OCT images of intact fruit from five commercial cultivars. Visualisation and characterisation of large parenchyma cells in the outer pericarp of kiwifruit was achieved by developing an automated image processing technique. This work established the usefulness of OCT to perform rapid analysis and differentiation of the microstructures of sub-surface cells between kiwifruit cultivars. However, the effects of preharvest conditions between batches of fruit within a cultivar were not detectable from image analysis and hence, the ability to provide segregation or prediction for fruit from the same cultivar was assumed to be limited. Total soluble solids concentration (TSS) and flesh firmness (FF) are two important quality attributes indicating the eating quality and storability of stored kiwifruit. Prediction of TSS and FF using non-destructive techniques would allow strategic marketing of fruit. This work demonstrated that visible-near-infrared (Vis-NIR) spectroscopy could be utilised as the sole input at harvest, to provide quantitative prediction of post-storage TSS by generating blackbox regression models. However the level of accuracy achieved was not adequate for online sorting purposes. Quantitative prediction of FF remained unsuccessful. Improved ways of physical measurements for FF may help reduce the undesirable variation observed on the same fruit and increase prediction capability. More promising results were obtained by developing blackbox classification models using Vis-NIR spectroscopy at harvest to segregate storability of individual kiwifruit based on the export FF criterion of 1 kgf (9.8 N). Through appropriate machine learning techniques, the surface properties of fruit at harvest captured in the form of spectral data were correlated to post-storage FF via pattern recognition. The best prediction was obtained for fruit stored at 0°C for 125 days: approximately 50% of the soft fruit and 80% of the good fruit could be identified. The developed model was capable of performing classification both within (at the fruit level) and between grower lines. Model validation suggested that segregation between grower lines at harvest achieved 30% reduction in soft fruit after storage. Should the model be applied in the industry to enable sequential marketing, $11.2 million NZD/annum could be saved because of reduced fruit loss, repacking and condition checking costs