Optimum Illuminant Determination Based on Reduced and Optimized Multispectral Spectroscopy to Enhance Vein Detection

Venepuncture as a mode of gaining intravenous access has been a prime practice in surgical procedures and other conventional drug administering into a patient. Biomedical engineering has stressed relatively high scale of importance in the spectroscopic analysis of vein imaging as a sparky approach to promote a non-invasive catheterization. However, medical personnel are challenged by the physiological circumstances of skin tone, presence of scars and irregularity of the epidermal topology, when performing subcutaneous vein localization, which led them to increase number of insertion attempts. Hence, this paper proposes an optimized solution to provide enhanced visual aids for personnel to achieve successful vein catheterization at first attempt

Smartphone-based multispectral imaging: system development and potential for mobile skin diagnosis

We investigate the potential of mobile smartphone-based multispectral imaging for the quantitative diagnosis and management of skin lesions. Recently, various mobile devices such as a smartphone have emerged as healthcare tools. They have been applied for the early diagnosis of nonmalignant and malignant skin diseases. Particularly, when they are combined with an advanced optical imaging technique such as multispectral imaging and analysis, it would be beneficial for the early diagnosis of such skin diseases and for further quantitative prognosis monitoring after treatment at home. Thus, we demonstrate here the development of a smartphone-based multispectral imaging system with high portability and its potential for mobile skin diagnosis. The results suggest that smartphone-based multispectral imaging and analysis has great potential as a healthcare tool for quantitative mobile skin diagnosis. © 2016 Optical Society of America.1

Optimum Illuminant Determination Based on Reduced and Optimized Multispectral Spectroscopy to Enhance Vein Detection

Venepuncture as a mode of gaining intravenous access has been a prime practice in surgical procedures and other conventional drug administering into a patient. Biomedical engineering has stressed relatively high scale of importance in the spectroscopic analysis of vein imaging as a sparky approach to promote a non-invasive catheterization. However, medical personnel are challenged by the physiological circumstances of skin tone, presence of scars and irregularity of the epidermal topology, when performing subcutaneous vein localization, which led them to increase number of insertion attempts. Hence, this paper proposes an optimized solution to provide enhanced visual aids for personnel to achieve successful vein catheterization at first attempt

Numerical Demultiplexing of Color Image Sensor Measurements via Non-linear Random Forest Modeling

Due to recent advancements in technology, consumer digital cameras are becoming cheaper and easier to use. These consumer digital cameras, with Bayer color filter arrays (CFAs), allow for simultaneous capture of the red, green and blue (RGB) channels. To achieve higher spectral resolution, multispectral imaging systems use methods such as filter wheels and tunable filters to capture data in a sequential manner. However, in order to capture transient phenomena, one would need to capture spectral information of a 2D scene in a simultaneous manner. Therefore, there has been an on-going trend towards creating a simultaneous multispectral imaging system that uses a conventional consumer digital camera with a Bayer CFA. Such a system allows for a effective imaging of transient or dynamic phenomena with a low-cost and compact system. Currently, the main method to accomplish this is known as Wiener estimation which uses statistical assumptions of the relationship between the incoming spectra and the RGB measurements. However, these assumptions limit the ability to accurately predict the incoming spectra. Therefore, we leverage a comprehensive framework based on numerical demultiplexing of sensor measurements via spectral characterization of the image sensor CFA and non-linear random forest modeling. To create this numerical demultiplexing system we create a forward model from the spectral sensitivity of the imaging system, which is accomplished with a monochrometer. This forward model is then used to create a mapping of 10,000 randomly generated spectra to their corresponding RGB values. This mapping acts as our training set for our non-linear inverse model which utilizes the random forest modeling framework. Having constructed the numerical demultiplexer, we test the performance against the state-of-the-art Wiener estimation for both quantitative and qualitative experiments. In the first set of experiments, we performed a quantitative performance assessment of the proposed framework within a controlled simulation environment. The second set of experiments, validated the observations made from the first set of controlled simulation experiments within a real-world setting. More specifically, we used an icon with different colors as well as a scene of different color flowers to perform quantitative analysis. In these experiments, we show that the proposed numerical demultiplexer outperforms the state-of-the art and is a more robust and reliable way to infer higher spectra from RGB measurements. Having validated the numerical demultiplexer, we use it for two applications which are photoplethysmogrpahic imaging and multispectral microscopy. For photoplethysmogrpahic imaging we found that decomposing the RGB camera measurements into narrow-band spectral information can noticeably improve the prediction of heart rate estimation. In addition, we used the numerical demultiplexer for both a bright-field multispectral microscope as well as a dark-field fluorescence multispectral microscope, which illustrates its potential as a low-cost, portable, point-of-care system

Vein visualization using a smart phone with multispectral wiener estimation for point-of-care applications

Effective vein visualization is clinically important for various point-of-care applications, such as needle insertion. It can be achieved by utilizing ultrasound imaging or by applying infrared laser excitation and monitoring its absorption. However, while these approaches can be used for vein visualization, they are not suitable for point-of-care applications because of their cost, time, and accessibility. In this paper, a new vein visualization method based on multispectral Wiener estimation is proposed and its real-time implementation on a smart phone is presented. In the proposed method, a conventional RGB camera on a commercial smart phone (i.e., Galaxy Note 2, Samsung Electronics Inc., Suwon, Korea) is used to acquire reflectance information from veins. Wiener estimation is then applied to extract the multispectral information from the veins. To evaluate the performance of the proposed method, an experiment was conducted using a color calibration chart (ColorChecker Classic, X-rite, Grand Rapids, MI, USA) and an average root-mean-square error of 12.0% was obtained. In addition, an in vivo subcutaneous vein imaging experiment was performed to explore the clinical performance of the smart phone-based Wiener estimation. From the in vivo experiment, the veins at various sites were successfully localized using the reconstructed multispectral images and these results were confirmed by ultrasound B-mode and color Doppler images. These results indicate that the presented multispectral Wiener estimation method can be used for visualizing veins using a commercial smart phone for point-of-care applications (e.g., vein puncture guidance)

Libro de actas. XXXV Congreso Anual de la Sociedad Española de Ingeniería Biomédica

596 p.CASEIB2017 vuelve a ser el foro de referencia a nivel nacional para el intercambio científico de conocimiento, experiencias y promoción de la I D i en Ingeniería Biomédica. Un punto de encuentro de científicos, profesionales de la industria, ingenieros biomédicos y profesionales clínicos interesados en las últimas novedades en investigación, educación y aplicación industrial y clínica de la ingeniería biomédica. En la presente edición, más de 160 trabajos de alto nivel científico serán presentados en áreas relevantes de la ingeniería biomédica, tales como: procesado de señal e imagen, instrumentación biomédica, telemedicina, modelado de sistemas biomédicos, sistemas inteligentes y sensores, robótica, planificación y simulación quirúrgica, biofotónica y biomateriales. Cabe destacar las sesiones dedicadas a la competición por el Premio José María Ferrero Corral, y la sesión de competición de alumnos de Grado en Ingeniería biomédica, que persiguen fomentar la participación de jóvenes estudiantes e investigadores