Spectral filter array cameras as a diagnostic skin imaging tool
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Skin is the human’s largest organ and has many vital functions including protection from pathogens, temperature regulation, touch sensation, vitamin D synthesis and protecting the water inside the body. It does not only protect the body from the environment but also carries information about the health of individuals. Diagnosis and monitoring of skin and vital functions measured in non-contact is a broad field of research. Measuring vital signs, monitoring oxygenation and skin diagnosis can benefit from spatially resolved images of the tissue. Standard three channel colour imaging provides the ease of use and acquisition speed for a clinical setup but lacks the spectral resolution to identify specific narrow bands of interest containing the essential information. Spectral imaging has been used to quantify diagnostically relevant physical properties of living tissue but suffers from slow acquisition speed and time delays between the acquisition of different bands. Recent sensor development has led to so-called spectral filter array (SFA) cameras, which combine the acquisition speed and ease of use of standard RGB imaging with the spectral resolution of spectral cameras. To utilise all the benefits of this new imaging modality, additional processing steps are required. This thesis explores SFA imaging in the context of skin diagnosis, and the imaging is enhanced with physical skin simulation models. Skin models based on Monte Carlo simulation allow change and control over optical properties and resulting spectral reflectance from skin can be recorded. The simulated spectral reflectance with known optical properties is used in three different ways within this research. First, they are tested, by studying the impact of the optical properties on a resulting colour patch. This provides a better understanding of the relationship between colour shade and different combinations of optical properties. Secondly, the simulations are used to enhance the interpretability of spectral measurements regarding important physical skin properties with diagnostic value. This approach is applied to two different spectral filter array cameras and an RGB imager in conjunction with multiple LEDs. Thirdly, skin simulations are performed to generate an exhaustive spectral reflectance database, for training and enhancement of spectral reconstructions of skin reflectance. This specialised database covers a wide range of physically, but not physiologically possible optical properties. Different spectral imagers in the visual and near-infrared spectrum are applied to measuring oxygenation spatially resolved in living tissue. Additionally, a processing framework is proposed for spectral filter array cameras. This framework combines several SFA camera-specific processing steps and shows transferability to other cameras. It is tested by comparing oxygenation estimations from both a visual range (VIS) and a near-infrared (NIRS) spectral filter array camera with the de facto clinical standard in an upper arm occlusion test. Finally, this work proposes a framework for selecting and testing SFA cameras for skin diagnosis tasks without the need of (extensive) clinical studies. This framework could aid in the development of SFA cameras for specific tasks and explores currently commercially available models for skin oxygenation measurements. In the future, it can be expected that spectral filter array cameras will become cheaper and more common. This work establishes a solid foundation for applying this new versatile form of spectral imaging in the context of skin diagnosis. Both general practitioners, dermatologists and, anesthesiologists can benefit from an easy to use, spatially resolved, real-time oxygenation measurement tool.
Has partsPaper A: Bauer, Jacob Renzo; Pedersen, Marius; Hardeberg, Jon Yngve; Verdaasdonk, Rudolf. Skin color simulation - review and analysis of available Monte Carlo-based photon transport simulation models. I: CIC25, 25th Color and Imaging Conference: Color Science and Engineering Systems, Technologies, and Applications. The Society for Imaging Science and Technology 2017 ISBN 9780892083275. s. 165-170
Paper B: Bauer, Jacob Renzo; Hardeberg, Jon Yngve; Verdaasdonk, Rudolf. Optical skin assessment based on spectral reflectance estimation and Monte Carlo simulation. Proceedings of SPIE, the International Society for Optical Engineering 2017 ;Volum 10057.
Paper C: Bauer, Jacob Renzo; Bruins, Arnoud A.; Hardeberg, Jon Yngve; Verdaasdonk, Rudolf. A Spectral Filter Array Camera for Clinical Monitoring and Diagnosis: Proof of Concept for Skin Oxygenation Imaging. Journal of Imaging 2019 ;Volum 5(8)
Paper D: Bauer, Jacob Renzo; van Beekum, Karlijn; Klaessens, John; Noordmans, Herke Jan; Boer, Christa; Hardeberg, Jon Yngve; Verdaasdonk, Rudolf. Towards real-time non contact spatial resolved oxygenation monitoring using a multi spectral filter array camera in various light conditions. Proceedings of SPIE, the International Society for Optical Engineering 2018 ;Volum 10489:10490O. s. 1-9
Paper E: Bauer, Jacob Renzo; Thomas, Jean-Baptiste; Hardeberg, Jon Yngve; Verdaasdonk, Rudolf M.. An Evaluation Framework for Spectral Filter Array Cameras to Optimize Skin Diagnosis. Sensors 2019 ;Volum 19.(21)
Paper F: Bruins, Arnoud A.; Geboers, Diederik G. P. J.; Bauer, Jacob Renzo; Klaessens, John; Verdaasdonk, R.M.; Boer, Christa. The vascular occlusion test using multispectral imaging: a validation study. Journal of clinical monitoring and computing 2020 s. 1-9