This PDF file contains the front matter associated with SPIE Proceedings Volume 10485 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

Blood quality and safety management is a critical issue for cold chain transportation of blood or blood-based biological reagent. The conventional methods of blood alteration severity assessment mainly rely on kit test or blood-gas analysis required opening the blood package to get samples, which cause possible blood pollution and are complicate, timeconsuming, and expensive. Here we proposed to develop a portable, real-time, safety, easy-operated and low cost method aimed at assessing blood alteration severity. Color images of the blood in transparent blood bags were collected with a smartphone and the alteration severity of the blood was assessed by the smartphone app offered analysis of RGB color values of the blood. The algorithm is based on a large number sample of RGB values of blood at different alteration degree. The blood quality results evaluated by the smartphone are in accordance with the actual data. This study indicates the potential of smart phone in real time, convenient, and reliable blood quality assessment.

Mobile phones come equipped with a vast array of actuation and sensing technologies, making them an ideal platform for point-of-care diagnostics and information gathering. Mobile phone microscopes take advantage of the small pixel size on mobile phone camera sensors for micron-scale resolution. Focusing can be achieved with built-in autofocus and image processing can be done on-board, however, the illumination is typically introduced via an external light emitting diode (LED). These external LEDs are typically externally powered, adding bulk and cost to a system that is meant to be as affordable as possible. In this work, we present a mobile phone microscope that uses the phone's integrated flash as an illumination source, eliminating the need to engineer an external illumination into the system. Our design consists of a 3D printed clip-on module containing a lens, which together with the mobile phone camera lens acts as an infinite-conjugate microscope. The clip-on module functions as a basic sample holder, and contains a series of light tunnels that redirect light from the flash through the sample for brightfield illumination. Instead of mirrors and a condenser lens, diffuse reflection from the internal light tunnel of the plastic clip-on module both reflects and scatters light into a range of illumination angles – ideal for brightfield microscopy. For low-contrast samples, darkfield imaging is achieved with ambient lighting via internal reflection within the sample microscope slide. We demonstrate imaging and video microscopy of a range of samples including plants, cell cultures and cattle semen.

Extreme or prolonged neonatal jaundice (hyperbilirubinemia) can result in permanent neurological impairment and even death. In developing countries, risk factors that increase the risk of neurodevelopmental impairment, such as sepsis, malnutrition, and certain genetic conditions are common. Administering treatments can be simple but identification of at-risk infants through visual screening is unreliable. Infants in the US are routinely screened prior to hospital discharge using transcutaneous bilirubinometry (TcB), a non-invasive technique based on diffuse reflectance. In low-resource settings such as rural sub-Saharan Africa, TcB devices are not available to traditional birth attendants and doctors; however, it is increasingly common for these personnel to carry mobile phones equipped with a camera and flash. We have previously reported initial feasibility of TcB utilizing the built-in camera and flash of the mobile phone, a Monte Carlo model driven design of a snap-on optical assembly. Here, we report the experience and results from clinical studies in newborns which compare mobile-phone based measurements of TcB with corresponding serum bilirubin levels. These results will lead to a discussion of feasibility and limitations for mobile-phone based TcB.

Cervical cancer is the fourth most common cancer among women worldwide and is especially prevalent in low resource settings due to lack of screening and treatment options. Visual inspection with acetic acid (VIA) is a widespread and cost-effective screening method for cervical pre-cancer lesions, but accuracy depends on the experience level of the health worker. Digital cervicography, capturing images of the cervix, enables review by an off-site expert or potentially a machine learning algorithm. These reviews require images of sufficient quality. However, image quality varies greatly across users. A novel algorithm was developed to evaluate the sharpness of images captured with the MobileODT’s digital cervicography device (EVA System), in order to, eventually provide feedback to the health worker. The key challenges are that the algorithm evaluates only a single image of each cervix, it needs to be robust to the variability in cervix images and fast enough to run in real time on a mobile device, and the machine learning model needs to be small enough to fit on a mobile device’s memory, train on a small imbalanced dataset and run in real-time. In this paper, the focus scores of a preprocessed image and a Gaussian-blurred version of the image are calculated using established methods and used as features. A feature selection metric is proposed to select the top features which were then used in a random forest classifier to produce the final focus score. The resulting model, based on nine calculated focus scores, achieved significantly better accuracy than any single focus measure when tested on a holdout set of images. The area under the receiver operating characteristics curve was 0.9459.

The world health organization recommends visual inspection with acetic acid (VIA) and/or Lugol’s Iodine (VILI) for cervical cancer screening in low-resource settings. Human interpretation of diagnostic indicators for visual inspection is qualitative, subjective, and has high inter-observer discordance, which could lead both to adverse outcomes for the patient and unnecessary follow-ups. In this work, we a simple method for automatic feature extraction and classification for Lugol’s Iodine cervigrams acquired with a low-cost, miniature, digital colposcope. Algorithms to preprocess expert physician-labelled cervigrams and to extract simple but powerful color-based features are introduced. The features are used to train a support vector machine model to classify cervigrams based on expert physician labels. The selected framework achieved a sensitivity, specificity, and accuracy of 89.2%, 66.7% and 80.6% with majority diagnosis of the expert physicians in discriminating cervical intraepithelial neoplasia (CIN +) relative to normal tissues. The proposed classifier also achieved an area under the curve of 84 when trained with majority diagnosis of the expert physicians. The results suggest that utilizing simple color-based features may enable unbiased automation of VILI cervigrams, opening the door to a full system of low-cost data acquisition complemented with automatic interpretation.

Methods of detection for key biomarkers in bodily fluids that are specific, low-cost, and non-invasive are in high demand for various biomedical applications. Specifically, field-portable and cost-effective devices which can enable these measurements to be made at home or in the field are crucial for practical and widespread use of these technologies. Plasmonic sensors form an emerging bio-sensor platform that responds to the specific adsorption of bio-molecules via a spectral change in transmission or reflection mode of operation. However, to read and quantify their spectral response, expensive and bulky optics such as broad-band light sources and high resolution spectrometers are typically employed, severely limiting their potential applications in resource-limited settings. In an effort to build low-cost and compact plasmonic readers, we have developed a computational sensing framework that uses machine learning to statistically differentiate the sensor’s spectral response from fabrication related variability and other noise factors, and select the optimal illumination bands for the lowest-possible read-out error. To validate this framework we constructed a low-cost and field-portable plasmonic reader around the optimal illumination bands selected for different plasmonic nano-hole array designs. We then validated the superior performance of our computational reader by measuring a large number of independently fabricated flexible plasmonic sensors made using scalable, nano-imprint lithography methods without the use of a clean room. Additionally, these structures can subsequently be transfer-printed onto disposable, wearable platforms where they can be chemically modified to specifically and sensitively capture target biomarkers in bio-fluids e.g., tear or sweat, enabling new applications in point-of-care diagnostics.

Image segmentation plays an important role in medical science. One application is multimodality imaging, especially the fusion of structural imaging with functional imaging, which includes CT, MRI and new types of imaging technology such as optical imaging to obtain functional images. The fusion process require precisely extracted structural information, in order to register the image to it. Here we used image enhancement, morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in deep learning way. Such approach greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. The contours of the borders of different tissues on all images were accurately extracted and 3D visualized. This can be used in low-level light therapy and optical simulation software such as MCVM. We obtained a precise three-dimensional distribution of brain, which offered doctors and researchers quantitative volume data and detailed morphological characterization for personal precise medicine of Cerebral atrophy/expansion. We hope this technique can bring convenience to visualization medical and personalized medicine.

Hyperspectral reflectance imaging (HRI) is an emerging clinical tool for characterizing spatial and temporal variations in blood perfusion and oxygenation for applications such as burn assessment, wound healing, retinal exams and intraoperative tissue viability assessment. Since clinical HRI-based oximeters often use near-infrared (NIR) light, NIR-enabled mobile phones may provide a useful platform for future point-of-care devices. Furthermore, quantitative NIR imaging on mobile phones may dramatically increase the availability and accessibility of medical diagnostics for low-resource settings. We have evaluated the potential for phone-based NIR oximetry imaging and elucidated factors affecting performance using devices from two different manufacturers, as well as a scientific CCD. A broadband light source and liquid crystal tunable filter were used for imaging at 10 nm bands from 650 to 1000 nm. Spectral sensitivity measurements indicated that mobile phones with standard NIR blocking filters had minimal response beyond 700 nm, whereas one modified phone showed sensitivity to 800 nm and another to 1000 nm. Red pixel channels showed the greatest sensitivity up to 800 nm, whereas all channels provided essentially equivalent sensitivity at longer wavelengths. Referencing of blood oxygenation levels was performed with a CO-oximeter. HRI measurements were performed using cuvettes filled with hemoglobin solutions of different oxygen saturation levels. Good agreement between absorbance spectra measured with mobile phone and a CCD cameras were seen for wavelengths below 900 nm. Saturation estimates showed root-mean-squared-errors of 5.2% and 4.5% for the CCD and phone, respectively. Overall, this work provides strong evidence of the potential for mobile phones to provide quantitative spectral imaging in the NIR for applications such as oximetry, and generates practical insights into factors that impact performance as well as test methods for performance assessment.

Cervical cancer is a leading cause of death for women in low resource settings. In order to better detect cervical dysplasia, a low cost multi-spectral colposcope was developed utilizing low costs LEDs and an area scan camera. The device is capable of both traditional colposcopic imaging and multi-spectral image capture. Following initial bench testing, the device was deployed to a gynecology clinic where it was used to image patients in a colposcopy setting. Both traditional colposcopic images and spectral data from patients were uploaded to a cloud server for remote analysis. Multi-spectral imaging (~30 second capture) took place before any clinical procedure; the standard of care was followed thereafter. If acetic acid was used in the standard of care, a post-acetowhitening colposcopic image was also captured. In analyzing the data, normal and abnormal regions were identified in the colposcopic images by an expert clinician. Spectral data were fit to a theoretical model based on diffusion theory, yielding information on scattering and absorption parameters. Data were grouped according to clinician labeling of the tissue, as well as any additional clinical test results available (Pap, HPV, biopsy). Altogether, N=20 patients were imaged in this study, with 9 of them abnormal. In comparing normal and abnormal regions of interest from patients, substantial differences were measured in blood content, while differences in oxygen saturation parameters were more subtle. These results suggest that optical measurements made using low cost spectral imaging systems can distinguish between normal and pathological tissues.

Worldwide, infectious diseases cause 16% of deaths each year. It is evident that in the past many of the deadly diseases originated in countries with little to none or fewer resources to contain the spread of the disease. To combat such diseases, improvements in nucleic acid testing (NAT) to enable rapid and accurate detection of viruses in low resources settings are needed. Current NAT instruments are bulky, expensive, and slow, limiting the potential for point-of-care applications. Here we present a portable spectrometer based system capable of performing quantitative NAT utilizing isothermal polymerase chain reaction (PCR) variants. A micro spectrometer used in the device enables the detection of a continuous fluorescence spectrum allowing multiplex detection of different DNA labeling dyes. Isothermal temperature is facilitated by cartridge heaters embedded in an aluminum block, which holds the standard PCR tube as the sample container. The device is pocket-sized and operates on a 9V battery, making it ideal for low-resource settings. To demonstrate the operation of the device, loop-mediated isothermal amplification (LAMP) of Kaposi’s sarcoma herpesvirus (KSHV) is performed at 68℃. Fluorescence emitted by the intercalating dye in the reaction is measured in real-time by the micro spectrometer. KSHV quantification is obtained in as little as 30 minutes. The device is intended for simultaneous detection of multiple DNA targets in the field.

Adulteration of milk for economic gains is a widespread issue throughout the developing world that can have far-reaching health and nutritional impacts. Milk analysis technologies, such as infrared spectroscopy, can screen for adulteration, but the cost of these technologies has prohibited their use in low resource settings. Recent developments in infrared and Raman spectroscopy hardware have led to commercially available low-cost devices. In this work, we evaluated the performance of two such spectrometers in detecting and quantifying the presence of milk adulterants. Five common adulterants – ammonium sulfate, melamine, sodium bicarbonate, sucrose, and urea, were spiked into five different raw cow and goat milk samples at different concentrations. Collected MIR and Raman spectra were analyzed using partial least squares regression. The limit of detection (LOD) for each adulterant was determined to be in the range of 0.04 to 0.28% (400 to 2800 ppm) using MIR spectroscopy. Raman spectroscopy showed similar LOD’s for some of the adulterants, notably those with strong amine group signals, and slightly higher LOD’s (up to 1.0%) for other molecules. Overall, the LODs were comparable to other spectroscopic milk analyzers on the market, and they were within the economically relevant concentration range of 100 to 4000 ppm. These lower cost spectroscopic devices therefore appear to hold promise for use in low resource settings.

Supercontinuum (SC) light source is certainly one of the best option for ultra-high resolution optical coherence tomography (UHR-OCT). Over the last few years several demonstrations have been done for each commonly used wavelength range [1-2-3]. Nowadays, SC dedicated to UHR-OCT is a mature technology with turn-key commercially available system [4]. The new challenge to answer for SC source is the cost reduction one. In this study, we demonstrate that a Q-switched based SC (QS-SC) could be an alternative to the current state of the art SC based on a Mode-Locked laser (ML-SC). This QS-SC, whose cost is less than 15 % of the ML-SC, offers similar possibilities in terms of bandwidth, beam quality and optical density within the OCT band [5]. We demonstrate the usefulness of such a source by direct comparison with the ML-SC source commonly used. Our study includes a comparison of the pulse to pulse stability of both sources over the OCT wavelength range, where it is shown that the QS-SC is much more stable than the ML-SC. Also, a noise analysis conducted from the OCT point of view shows that the source repetition rate is a key parameter for any SC based OCT system. A comparison of images acquired from biological and non-biological samples is performed with emphasis on their contrast. Our conclusion is that a QS-SC can be used a useful source for UHR-OCT if compromise can be done in terms of speed of the detection unit. Finally, our study has been done at a central wavelength of 1270 nm, however the ultra-broad flat spectrum of the QS-SC makes it an interesting source for the 800 nm or visible range OCT too, opening the door for low-cost multi-band or multi-modal OCT. REFERENCES 1. K. Bizheva, B. Tan, B. MacLelan, O. Kralj, M. Hajialamdari, D. Hileeto, and L. Sorbara, “Sub-micrometer axial resolution OCT for in-vivo imaging of the cellular structure of healthy and keratoconic human corneas,” Biomed. Opt. Express 8, 800-812 (2017). 2. W. Yuan, J. Mavadia-Shukla, J. Xi, W. Liang, X. Yu, S. Yu, and X. Li, "Optimal operational conditions for supercontinuum-based ultrahigh-resolution endoscopic OCT imaging," Opt. Lett. 41, 250-253 (2016). 3. C. Cheung, J. Daniel, M. Tokurakawa, W. Clarkson, and H. Liang, "High resolution Fourier domain optical coherence tomography in the 2 μm wavelength range using a broadband supercontinuum source," Opt. Express 23, 1992-2001 (2015). 4. http://www.nktphotonics.com/lasers-fibers/product/superk-oct-broadband-sources-optical-coherence-tomography/ 5. http://www.nktphotonics.com/lasers-fibers/product/superk-compact-supercontinuum-lasers/

Healthcare access in low-resource settings is compromised by the availability of affordable and accurate diagnostic equipment. The four primary poverty-related diseases – AIDS, pneumonia, malaria, and tuberculosis - account for approximately 400 million annual deaths worldwide as of 2016 estimates. Current diagnostic procedures for these diseases are prolonged and can become unreliable under various conditions. We present the development of a simple low-cost UV fluorescence multi-spectral imaging system geared towards low resource settings for a variety of biological and in-vitro applications. Fluorescence microscopy serves as a useful diagnostic indicator and imaging tool. The addition of a multi-spectral imaging modality allows for the detection of fluorophores within specific wavelength bands, as well as the distinction between fluorophores possessing overlapping spectra. The developed instrument has the potential for a very diverse range of diagnostic applications in basic biomedical science and biomedical diagnostics and imaging. Performance assessment of the microscope will be validated with a variety of samples ranging from organic compounds to biological samples.

Development of portable and cost-effective optical imaging devices is essential for quantification of molecular bioassays at the point of care (POC). Mobile phone-based microscopy tools have shown great potential as biomedical reader platforms due to their small size, large distribution volume, and constantly improving optical properties. However, the optical detection sensitivity remains a challenge to further improve the diagnostic capabilities of microscopy and sensing devices based on mobile-phones. Here, we demonstrate a simple strategy to enhance the signal intensity of a smartphone fluorescence microscope by approximately an order of magnitude using surface-enhanced fluorescence (SEF) created by a thin silver film. This plasmonics-enhanced smartphone microscopy platform relies on an opto-mechanical attachment based on the Kretschmann configuration, where the sample is placed on a silver-coated glass coverslip and excited by a laser diode from the backside through a glass hemisphere. The fluorescence enhancement effect was systematically optimized by tuning the metal film thickness, spacer distance, excitation angle, and polarization, and experimentally validated by comparison to theoretical simulations. With this mobile device, single fluorescent beads as small as 50 nm and individual quantum dots (ca. 20 nm dia.) were detected. We further quantified the sensitivity limit of this mobile platform to be around 80 fluorophores per diffraction-limited spot by imaging DNA origami based brightness standards labeled with different numbers of fluorophores. We believe that this SEF-based mobile microscopy platform opens up various new opportunities for POC diagnostics and sensing applications in resource-limited-settings.

Publisher’s Note: This paper, originally published on 2/13/2018, was replaced with a corrected/revised version on 10/2/2018. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.

Preliminary diagnosis of closely resembling skin conditions can be highly subjective for dermatologists. In ambiguous cases, it often leads to performing invasive procedures like biopsies. Different skin conditions, however, have varying concentrations of fluorophores (like collagen, NADH) and chromophores (like melanin, hemoglobin) which can alter their fluorescence spectra. We demonstrate a handheld, portable, smartphone-based spectrometer that leverages these alterations in skin autofluorescence spectra for rapid screening of skin conditions. This methodology involves excitation of affected skin areas with ultraviolet (UV-A) 385 nm light, capturing the generated fluorescence spectra and sending the data wirelessly to a companion mobile application for data storage, analysis and visualization. By collecting the fluorescence spectral signals from healthy and unhealthy skin conditions, we establish that the signals collected using this portable device can be used to develop a classification method to help in differentially diagnosing these conditions. It shows promise as a useful skin screening tool for both dermatologists and primary health care workers. This device can enable quick, non-invasive and a more objective preliminary examination. We envision the device to be especially useful in primary healthcare centers of developing countries where availability of dermatologists is limited.

The use of mobile phones to conduct diagnostic microscopy at the point-of-care presents intriguing possibilities for the advancement of high-quality medical care in remote settings. However, it is challenging to create a single device that can adapt to the ever-varying camera technologies in phones or that can image with the customization that multiple modalities require for applications such as malaria diagnosis. A portable multi-modal microscope system is presented that utilizes a Raspberry Pi to collect and transmit data wirelessly to a myriad of electronic devices for image analysis. The microscopy system is capable of providing to the user correlated brightfield, polarized, and fluorescent images of samples fixed on traditional microscopy slides. The multimodal diagnostic capabilities of the microscope were assessed by measuring parasitemia of Plasmodium falciparum-infected thin blood smears. The device is capable of detecting fluorescently-labeled DNA using FITC excitation (490 nm) and emission (525 nm), the birefringent P. falciparum byproduct hemozoin, and detecting brightfield absorption with a resolution of 0.78 micrometers (element 9-3 of a 1951 Air Force Target). This microscopy system is a novel portable imaging tool that may be a viable candidate for field implementation if challenges of system durability, cost considerations, and full automation can be overcome.

Fluorescence sensing through skin using wearable and cost-effective sensors can enable numerous biomedical applications, including continuous monitoring and quantification of biomarkers in conjunction with embedded fluorescent biosensors. Strong autofluorescence of the skin and its varying temporal response to excitation make it challenging to achieve highly sensitive fluorescence sensing at the visible part of the electromagnetic spectrum. Here, we demonstrate a compact, cost-effective and light-weight fluorescence imaging system for quantitative sensing through a highly autofluorescent, scattering and absorbing medium. We built a mobile fluorescence microscope weighing < 40 grams to sensitively quantify the concentration of fluorescent dyes through a skin tissue phantom. The optical characteristics of the skin phantom, such as scattering, absorption, and autofluorescence were designed to closely resemble the characteristics of human skin. In order to separate the target fluorescence emission signal from the tissue phantom’s autofluorescence we utilized an oblique Gaussian excitation profile, and performed our processing in the spatial frequency domain. Using an excitation intensity that is 8-fold below the safe exposure limit determined for human skin, we detected and quantified the concentration of Alexa 647 dye molecules in a microfluidic reservoir (with a volume of 0.01 µl) that is positioned 0.5 mm and 2 mm underneath our skin phantom, and achieved a detection limit of ~106 pg/ml and 5.3 ng/ml, respectively. Our method is also robust to lateral misalignments between the sample and the imaging device, with e.g., ~2-fold loss in limit of detection for ~0.6 mm lateral misalignment.

KRAS mutation is a common point mutation which occurs in ~30% of all human cancers. Early assessment of KRAS mutation status is critical for prediction of clinical treatment outcomes. However, current diagnostic methods are based on either polymerase-chain-reaction (PCR) or next-generation-sequencing (NGS) analysis of biopsy samples, which are complex, time consuming, and lack portability. Here, we report a cost-effective smartphone-based fluorescence microscopy platform for detection of KRAS point mutations by imaging targeted DNA sequencing reactions in preserved tumor slides. Smartphone-based KRAS mutation detection was conducted in two steps: 1) in situ rolling-circle-amplification (RCA) combined with ligation chemistry to label wild type/mutant strains with different fluorescent colors, and 2) rapidly scanning the sample by a smartphone microscope to quantify mutant-to-wild type ratios. This smartphone microscope contains two laser diodes (532 and 638 nm) for dual-color fluorescence detection (Cy3 & Cy5) and an additional white LED for brightfield imaging. We first imaged and analyzed synthetic or extracted DNA from model cell lines captured and amplified on glass slides. The smartphone fluorescence microscope was able to detect as low as 1fM target DNA sequence, and demonstrated a high sequencing depth (1:1000 mutant:wild type ratio), comparable to the sensitivity of FDA-approved KRAS PCR-based tests. Furthermore, the device was applied for in situ mutation detection in cell lines and real patient tumor slices. A machine learning algorithm was also developed to improve the recognition of target signals against the nonspecific background. Overall, smartphone-based in situ mutation detection resulted in 100% concordance to clinical NGS analysis.

Forest fires are a major source of particulate matter (PM) air pollution on a global scale. The composition and impact of PM are typically studied using only laboratory instruments and extrapolated to real fire events owing to a lack of analytical techniques suitable for field-settings. To address this and similar field test challenges, we developed a mobilemicroscopy- and machine-learning-based air quality monitoring platform called c-Air, which can perform air sampling and microscopic analysis of aerosols in an integrated portable device. We tested its performance for PM sizing and morphological analysis during a recent forest fire event in La Tuna Canyon Park by spatially mapping the PM. The result shows that with decreasing distance to the fire site, the PM concentration increases dramatically, especially for particles smaller than 2 µm. Image analysis from the c-Air portable device also shows that the increased PM is comparatively strongly absorbing and asymmetric, with an aspect ratio of 0.5–0.7. These PM features indicate that a major portion of the PM may be open-flame-combustion-generated element carbon soot-type particles. This initial small-scale experiment shows that c-Air has some potential for forest fire monitoring.

Diabetic peripheral neuropathy (DPN) accounts for around 73,000 lower-limb amputations annually in the US on patients with diabetes. Early detection of DPN is critical. Current clinical methods for diagnosing DPN are subjective and effective only at later stages. Until recently, thermal cameras used for medical imaging have been expensive and hence prohibitive to be installed in primary care setting. The objective of this study is to compare results from a low-cost thermal camera with a high-end thermal camera used in screening for DPN. Thermal imaging has demonstrated changes in microvascular function that correlates with nerve function affected by DPN. The limitations for using low-cost cameras for DPN imaging are: less resolution (active pixels), frame rate, thermal sensitivity etc. We integrated two FLIR Lepton (80x60 active pixels, 50° HFOV, thermal sensitivity < 50mK) as one unit. Right and left cameras record the videos of right and left foot respectively. A compactible embedded system (raspberry pi3 model Bv1.2) is used to configure the sensors, capture and stream the video via ethernet. The resulting video has 160x120 active pixels (8 frames/second). We compared the temperature measurement of feet obtained using low-cost camera against the gold standard highend FLIR SC305. Twelve subjects (aged 35-76) were recruited. Difference in the temperature measurements between cameras was calculated for each subject and the results show that the difference between the temperature measurements of two cameras (mean difference=0.4, p-value=0.2) is not statistically significant. We conclude that the low-cost thermal camera system shows potential for use in detecting early-signs of DPN in under-served and rural clinics.

Rhinolaryngoscopy remains difficult to perform in resource-limited settings due to the high cost of purchasing and maintaining equipment as well as the need for specialists to interpret exam findings. While the lack of expertise can be obviated by adopting telemedicine-based approaches, the capture, storage, and sharing of images/video is not a common native functionality of medical devices. Most rhinolaryngoscopy systems consist of an endoscope that interfaces with the patient’s naso/oropharynx, and a tower of modules that record video/images. However, these expensive and bulky modules can be replaced by a smartphone that can fulfill the same functions but at a lower cost. To demonstrate this, a commercially available rhinolaryngoscope was coupled to a smartphone using a 3D-printed adapter. Software developed for other clinical applications was repurposed for ENT use, including an application that controls image and video capture, a HIPAA-compliant image/video storage and transfer cloud database, and customized software features developed to improve practitioner competency. Audio recording capabilities to assess speech pathology were also integrated into the smartphone rhinolaryngoscope system. The illumination module coupled onto the endoscope remained unchanged. The spatial resolution of the rhinolaryngoscope system was defined by the fiber diameter of endoscope fiber bundle, rather than the smartphone camera. The mobile rhinolaryngoscope system was used with appropriate patients by a general practitioner in an office setting. The general practitioner then consulted with an ENT specialist via the HIPAA compliant cloud database and workflow modules on difficult cases. These results suggest the smartphone-based rhinolaryngoscope holds promise for use in low-resource settings.

Light-Assisted Drying (LAD) is a novel biopreservation technique which allows proteins to be immobilized in a dry, amorphous solid at room temperature. Indicator proteins are used in a variety of diagnostic assays ranging from highthroughput 96-well plates to new microfluidic devices. A challenge in the development of protein-based assays is preserving the structure of the protein during production and storage of the assay, as the structure of the protein is responsible for its functional activity. Freeze-drying or freezing are currently the standard for the preservation of proteins, but these methods are expensive and can be challenging in some environments due to a lack of available infrastructure. An inexpensive, simple processing method that enables supra-zero temperature storage of proteins used in assays is needed. Light-assisted drying offers a relatively inexpensive method for drying samples. Proteins suspended in a trehalose solution are dehydrated using near-infrared laser light. The laser radiation speeds drying and as water is removed the sugar forms a protective matrix. The goal of this study is optically characterize samples processed with LAD. We use polarized light imaging (PLI) to look at crystallization kinetics of samples and determine optimal humidity. PLI shows a 62.5% chance of crystallization during LAD processing and negligible crystallization during low RH storage.

Mueller Matrix polarimetry can provide useful information about the function and structure of the extracellular matrix. Mueller Matrix systems are sophisticated and costly optical tools that have been used primarily in the laboratory or in hospital settings. Here we introduce a low-cost snapshot Mueller Matrix polarimeter that that does not require external power, has no moving parts, and can acquire a full Mueller Matrix in less than 50 milliseconds. We utilized this technology in the study of cervical cancer in Mysore India, yet the system could be translated in multiple diagnostic applications.

Traditional pathology relies on tissue biopsy, micro-sectioning, immunohistochemistry and microscopic imaging, which are relatively expensive and labor-intensive, and therefore are less accessible in resource-limited areas. Low-cost tissue clearing techniques, such as the simplified CLARITY method (SCM), are promising to potentially reduce the cost of disease diagnosis by providing 3D imaging and phenotyping of thicker tissue samples with simpler preparation steps. However, the mainstream imaging approach for cleared tissue, fluorescence microscopy, suffers from high-cost, photobleaching and signal fading. As an alternative approach to fluorescence, here we demonstrate 3D imaging of SCMcleared tissue using on-chip holography, which is based on pixel-super-resolution and multi-height phase recovery algorithms to digitally compute the sample’s amplitude and phase images at various z-slices/depths through the sample. The tissue clearing procedures and the lens-free imaging system were jointly optimized to find the best illumination wavelength, tissue thickness, staining solution pH, and the number of hologram heights to maximize the imaged tissue volume, minimize the amount of acquired data, while maintaining a high contrast-to-noise ratio for the imaged cells. After this optimization, we achieved 3D imaging of a 200-μm thick cleared mouse brain tissue over a field-of-view of <20mm² , and the resulting 3D z-stack agrees well with the images acquired with a scanning lens-based microscope (20× 0.75NA). Moreover, the lens-free microscope achieves an order-of-magnitude better data efficiency compared to its lens-based counterparts for volumetric imaging of samples. The presented low-cost and high-throughput lens-free tissue imaging technique enabled by CLARITY can be used in various biomedical applications in low-resource-settings.

Nanoparticle and biomolecule imaging has become an important need for various applications. In an effort to find a higher throughput alternative to existing devices, we have designed a lensfree on-chip holographic imaging platform operating at an ultraviolet (UV) wavelength of 266 nm. With a custom-designed free-space light delivery system to illuminate the sample that is placed very close (<0.5 mm) to an opto-electronic image sensor chip, without any imaging lenses in between, the full active area of the imager chip (>16 mm² ) was utilized as the imaging field-of-view (FOV) capturing holographic signatures of target objects on a chip. These holograms were then digitally back propagated to extract both the amplitude and phase information of the sample. The increased forward scattering from nanoparticles due to this shorter illumination wavelength has enabled us to image individual particles that are smaller than 30 nm over an FOV of >16 mm² . Our platform was further utilized in high-contrast imaging of nanoscopic biomolecule aggregates since 266 nm illumination light is strongly absorbed by biomolecules including proteins and nucleic acids. Aggregates of Cu/Zn-superoxide dismutase (SOD1), which has been linked to a fatal neurodegenerative disease, ALS (amyotrophic lateral sclerosis), have been imaged with significantly improved contrast compared to imaging at visible wavelengths. This unique UV imaging modality could be valuable for biomedical applications (e.g., viral load measurements) and environmental monitoring including air and water quality monitoring.

Cervical cancer is the fourth most common cancer in women worldwide, with an estimated half a million new cases and 260,000 deaths each year. Developing countries bear about 84% of the global burden of the disease and 80% of the mortality due to a lack of effective screening programs. Cytology-based screening used in industrial countries is both expensive and difficult to implement in lower income countries with poor healthcare infrastructure and a shortage of pathologists. Low-cost optical technologies have been introduced in the low resource setting but to this date they are either hard to use single point measurements or require expert pathologist for image interpretation. Mueller Matrix imaging (MMI) is a novel imaging modality that uses polarized light to highlight subtle changes in cervical collagen structure typical of early stage cervical cancer. Recent ex-vivo work has shown that MMI is capable of up to 83% sensitivity and specificity in separating Cervical Intraepithelial Neoplasia stages. Unfortunately, the methodology requires a costly clinical colposcope with high encumbrance and low portability. We have developed a low cost portable Mueller Matrix imaging colposcope based on Savart platesthat can be deployed in a low resource setting and used by lay personnel. The device was used in the evaluation of cervical cancer risk in a pilot study of twenty-two volunteers in Mysore, India. The Papanicolaou test was used as a gold standard to in the validation of the polarimetric findings. Acceptability of the device by the patients was also ascertained. The development of a low cost and easy to use imaging system for the diagnosis of cervical cancer could be life changing for many women with poor or no access to specialized health care worldwide.

Apple quality grading is a critical issue in apple industry which is one economical pillar of many countries. Artificial grading is inefficient and of poor accuracy. Here we proposed to develop a portable, convenient, real-time, and low cost method aimed at grading apple. Color images of the apples were collected with a smartphone and the grade of sampled apple was assessed by a customized smartphone app, which offered the functions translating RGB color values of the apple to color grade and translating the edge of apple image to weight grade. The algorithms are based on modeling with a large number of apple image at different grades. The apple grade data evaluated by the smartphone are in accordance with the actual data. This study demonstrated the potential of smart phone in apple quality grading/online monitoring at gathering and transportation stage for apple industry.

Retinal abnormalities associated with hypertensive retinopathy are useful in assessing the risk of cardiovascular disease, heart failure, and stroke. Assessing these risks as part of primary care can lead to a decrease in the incidence of cardiovascular disease-related deaths. Primary care is a resource limited setting where low cost retinal cameras may bring needed help without compromising care. We compared a low-cost handheld retinal camera to a traditional table top retinal camera on their optical characteristics and performance to detect hypertensive retinopathy. A retrospective dataset of N=40 subjects (28 with hypertensive retinopathy, 12 controls) was used from a clinical study conducted at a primary care clinic in Texas. Non-mydriatic retinal fundus images were acquired using a Pictor Plus hand held camera (Volk Optical Inc.) and a Canon CR1-Mark II tabletop camera (Canon USA) during the same encounter. The images from each camera were graded by a licensed optometrist according to the universally accepted Keith-Wagener-Barker Hypertensive Retinopathy Classification System, three weeks apart to minimize memory bias. The sensitivity of the hand-held camera to detect any level of hypertensive retinopathy was 86% compared to the Canon. Insufficient photographer’s skills produced 70% of the false negative cases. The other 30% were due to the handheld camera’s insufficient spatial resolution to resolve the vascular changes such as minor A/V nicking and copper wiring, but these were associated with non-referable disease. Physician evaluation of the performance of the handheld camera indicates it is sufficient to provide high risk patients with adequate follow up and management.