Portable Imaging Research Articles

A Machine Learning-Based Classification Method for Monitoring Alzheimer’s Disease Using Electromagnetic Radar Data

Alzheimer’s and Parkinson’s diseases are two neurodegenerative brain disorders affecting more than 50 million people globally. Early diagnosis and appropriate assessment of disease progression are critical for treatment and improving patients’ health. Currently, the diagnosis of these neurodegenerative diseases is based primarily on mental status exams and neuroimaging scans, which are costly, time-consuming, and sometimes erroneous. Novel, cost-effective, and precise diagnostic tools and techniques are, thus, urgently required, particularly for early detection and prediction. In the recent decade, electromagnetic imaging has evolved as a cost-effective and noninvasive alternative approach for studying brain diseases. These studies focus on wearable and portable devices and imaging algorithms. However, microwave imaging cannot detect minimal changes in the brain at early stages accurately due to its lower resolution. This article investigates machine learning (ML) techniques for the early diagnosis of acute neurological diseases, especially Alzheimer’s disease (AD). A machine-learning-based classification method is proposed. Simulations are performed on realistic numerical brain phantoms using the CST studio suite to get the scattered signals. A novel data augmentation method is proposed to generate synthetic data required for ML algorithms. A deep neural network-based autoencoder extracts features to train various ML algorithms. The classification results are compared with raw data and manual feature extraction. The study shows that the proposed ML-based method could be used to monitor AD at its early stages.

Terahertz imaging for non-invasive classification of healthy and cimiciato-infected hazelnuts

The development of new non-invasive approaches able to recognize defective food is currently a lively field of research. In particular, a simple and non-destructive method able to recognize defective hazelnuts, such as cimiciato-infected ones, in real-time is still missing. This study has been designed to detect the presence of such damaged hazelnuts. To this aim, a measurement setup based on terahertz (THz) radiation has been developed. Images of a sample of 150 hazelnuts have been acquired in the low THz range by a compact and portable active imaging system equipped with a 0.14 THz source and identified as Healthy Hazelnuts (HH) or Cimiciato Hazelnut (CH) after visual inspection. All images have been analyzed to find the average transmission of the THz radiation within the sample area. The differences in the distribution of the two populations have been used to set up a classification scheme aimed at the discrimination between healthy and injured samples. The performance of the classification scheme has been assessed through the use of the confusion matrix on 50 samples. The False Positive Rate (FPR) and True Negative Rate (TNR) are 0% and 100%, respectively. On the other hand, the True Positive Rate (TPR) and False Negative Rate (FNR) are 75% and 25%, respectively. These results are relevant from the perspective of the development of a simple, automatic, real-time method for the discrimination of cimiciato-infected hazelnuts in the processing industry.

A Novel Portable, Mobile MRI: Comparison with an Established Low-Field Intraoperative MRI System.

Background MRI (magnetic resonance imaging) using low-magnet field strength has unique advantages for intraoperative use. We compared a novel, compact, portable MR imaging system to an established intraoperative 0.15 T system to assess potential utility in intracranial neurosurgery. Methods Brain images were acquired with a 0.15 T intraoperative MRI (iMRI) system and a 0.064 T portable MR system. Five healthy volunteers were scanned. Individual sequences were rated on a 5-point (1 to 5) scale for six categories: contrast, resolution, coverage, noise, artifacts, and geometry. Results Overall, the 0.064 T images (M = 3.4, SD = 0.1) had statistically higher ratings than the 0.15 T images (M = 2.4, SD = 0.2) ( p < 0.01). All comparable sequences (T1, T2, T2 FLAIR and SSFP) were rated significantly higher on the 0.064 T and were rated 1.2 points (SD = 0.3) higher than 0.15 T scanner, with the T2 fluid-attenuated inversion recovery (FLAIR) sequences showing the largest increment on the 0.064 T with an average rating difference of 1.5 points (SD = 0.2). Scanning time for the 0.064 T system obtained images more quickly and encompassed a larger field of view than the 0.15 T system. Conclusions A novel, portable 0.064 T self-shielding MRI system under ideal conditions provided images of comparable quality or better and faster acquisition times than those provided by the already well-established 0.15 T iMR system. These results suggest that the 0.064 T MRI has the potential to be adapted for intraoperative use for intracranial neurosurgery.

Cost-Effective Near Infrared Fluorescence Wide-Field Camera for Breast Tumor Imaging

Near-infrared (NIR) fluorescence imaging has long been proven useful for numerous medical applications, especially image-guided surgery since it can deeply penetrate tissue and acquire a fluorescence image from the FDA-approved fluorescence dye known as indocyanine green (ICG). NIR imaging-guided surgery can help enhance outcomes by better defining surgical margins and minimizing operative time. However, most commercial NIR fluorescence imaging systems are bulky and expensive. In this work, we introduce a low-cost and portable NIR fluorescence imaging system. The proposed system exploits an inexpensive complementary metal-oxide-semiconductor (CMOS) based on Nyxel® technology, considerably improving quantum efficiency (QE) in the NIR range. Therefore, it can acquire a NIR fluorescence image with outstanding quality. Furthermore, we conjugated ICG with nanoworm particles (NWs-ICG) since nanoparticle-conjugated dye can increase accumulation in a tumor. We show impressive applications of our system for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ex vivo</i> tissues and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> image-guided surgery using NWs-ICG as a contrast agent for breast tumors from transgenic mice.

Development and characterization of transfontanelle photoacoustic imaging system for detection of intracranial hemorrhages and measurement of brain oxygenation: Ex-vivo

We have developed and optimized an imaging system to study and improve the detection of brain hemorrhage and to quantify oxygenation. Since this system is intended to be used for brain imaging in neonates through the skull opening, i.e., fontanelle, we called it, Transfontanelle Photoacoustic Imaging (TFPAI) system. The system is optimized in terms of optical and acoustic designs, thermal safety, and mechanical stability. The lower limit of quantification of TFPAI to detect the location of hemorrhage and its size is evaluated using in-vitro and ex-vivo experiments. The capability of TFPAI in measuring the tissue oxygenation and detection of vasogenic edema due to brain blood barrier disruption are demonstrated. The results obtained from our experimental evaluations strongly suggest the potential utility of TFPAI, as a portable imaging modality in the neonatal intensive care unit. Confirmation of these findings in-vivo could facilitate the translation of this promising technology to the clinic.

Low‐Field Portable Magnetic Resonance Imaging for Post‐Thrombectomy Assessment of Ongoing Brain Injury

Background Timely imaging is essential for patients undergoing mechanical thrombectomy (MT). Our objective was to evaluate the safety and feasibility of low‐field portable magnetic resonance imaging (pMRI) for bedside evaluation following MT. Methods Patients with suspected large‐vessel occlusion undergoing MT were screened for eligibility. All pMRI examinations were conducted in the standard ferromagnetic environment of the interventional radiology suite. Clinical characteristics, procedural details, and pMRI features were collected. Subsequent high‐field conventional MRI within 72±12 hours was analyzed. If a conventional MRI was not available for comparison, computed tomography within the same time frame was used for validation. Results Twenty‐four patients were included (63% women; median age, 76 years [interquartile range, 69–84 years]). MT was performed with a median access to revascularization time of 15 minutes (interquartile range, 8–19 minutes), and with a successful outcome as defined by a thrombolysis in cerebral infarction score of ≥2B in 90% of patients. The median time from the end of the procedure to pMRI was 22 minutes (interquartile range, 16–32 minutes). The median pMRI examination time was 30 minutes (interquartile range, 17–33 minutes). Of 23 patients with available subsequent imaging, 9 had infarct progression compared with immediate post‐MT pMRI and 14 patients did not have progression of their infarct volume. There was no adverse event related to the examination. Conclusion Low‐field pMRI is safe and feasible in a post‐MT environment and enables timely identification of ischemic changes in the interventional radiology suite. This approach can facilitate the assessment of baseline infarct burden and may help guide physiological interventions following MT.

A portable, encapsulated microbial whole-cell biosensing system for the detection of bioavailable copper (II) in soil

A portable, field deployable whole-cell biosensor was developed that can withstand the complex matrices of soil and requires minimal to no sample preparation to monitor bioavailable concentrations of the essential micronutrient copper (II). Conventional measurement of micronutrients is often complex, laboratory-based, and not suitable for monitoring their bioavailable concentration. To address this need, we developed a fluorescence based microbial whole-cell biosensing (MWCB) system encoding for a Cu2+-responsive protein capable of generating a signal upon binding to Cu2+. The sensing-reporting protein was designed by performing circular permutation on the green fluorescent protein (GFP) followed by insertion of a Cu2+ binding motif into the structure of GFP. The design included insertion of several binding motifs and creating plasmids that encoded the corresponding sensing proteins. The signal generated by the sensing-reporting protein is directly proportional to the concentration of Cu2+ in the sample. Evaluation of the resulting biosensing systems carrying these plasmids was performed prior to selection of the optimal fluorescence emitting Cu2+-binding protein. The resulting optimized biosensing system was encapsulated in polyacrylate-alginate beads and embedded in soil for detection of the analyte. Once exposed to the soil, the beads were interrogated to measure the fluorescence signal emitted by the sensing-reporting protein using a portable imaging device. The biosensor was optimized for detection of Cu2+ in terms of selectivity, sensitivity, matrix effects, detection limits, and reproducibility in both liquid and soil matrices. The limit of detection (LoD) of the optimized encapsulated biosensor was calculated as 0.27 mg/L and 1.26 mg/kg of Cu2+ for Cu2+ in solution and soil, respectively. Validation of the portable imaging tools as a potential biosensing device in the field was performed.

Regional lung perfusion using different indicators in electrical impedance tomography.

Management of acute respiratory distress syndrome (ARDS) is classically guided by protecting the injured lung and mitigating damage from mechanical ventilation. Yet the natural history of ARDS is also dictated by disruption in lung perfusion. Unfortunately, diagnosis and treatment are hampered by the lack of bedside perfusion monitoring. Electrical impedance tomography is a portable imaging technique that can estimate regional lung perfusion in experimental settings from the kinetic analysis of a bolus of an indicator with high conductivity. Hypertonic sodium chloride has been the standard indicator. However, hypertonic sodium chloride is often inaccessible in the hospital, limiting practical adoption. We investigated whether regional lung perfusion measured using electrical impedance tomography is comparable between indicators. Using a swine lung injury model, we determined regional lung perfusion (% of total perfusion) in five pigs, comparing 12% sodium chloride to 8.4% sodium bicarbonate across stages of lung injury and experimental conditions (body position, positive end-expiratory pressure). Regional lung perfusion for four lung regions was determined from maximum slope analysis of the indicator-based impedance signal. Estimates of regional lung perfusion between indicators were compared in the lung overall and within four lung regions. Regional lung perfusion estimated with a sodium bicarbonate indicator agreed with a hypertonic sodium chloride indicator overall (mean bias 0%, limits of agreement -8.43%, 8.43%) and within lung quadrants. The difference in regional lung perfusion between indicators did not change across experimental conditions. Sodium bicarbonate may be a comparable indicator to estimate regional lung perfusion using electrical impedance tomography.NEW & NOTEWORTHY Electrical impedance tomography is an emerging tool to measure regional lung perfusion using kinetic analysis of a conductive indicator. Hypertonic sodium chloride is the standard agent used. We measured regional lung perfusion using another indicator, comparing hypertonic sodium chloride to sodium bicarbonate in an experimental swine lung injury model. We found strong agreement between the two indicators. Sodium bicarbonate may be a comparable indicator to measure regional lung perfusion with electrical impedance tomography.

Development of a Naked Eye CRISPR-Cas12a and -Cas13a Multiplex Point-of-Care Detection of Genetically Modified Swine.

The Rapid Visual CRISPR (RAVI-CRISPR) assay employs Cas12a and Cas13a enzymes for precise gene detection in a sample. However, RAVI-CRISPR is limited in single-tube multiplex detection applications due to the lack of specific single-strand (ss) DNA-fluorescently quenched (ssDNA-FQ) and RNA-fluorescently quenched (ssRNA-FQ) reporter cleavage mechanisms. We report the development of a sensitive and specific dual-gene Cas12a and Cas13a diagnostic system. To optimize the application for field testing, we designed a portable multiplex fluorescence imaging assay that could distinguish test results with the naked eye. Herein, dual gene amplified products from multiplex recombinase polymerase amplification (RPA) were simultaneously detected in a single tube using Cas12a and Cas13a enzymes. The resulting orthogonal DNA and RNA collateral cleavage specifically distinguishes individual and mixed ssDNA-FQ and ssRNA-FQ reporters using the green-red-yellow, fluorescent signal conversion reaction system, detectable with portable blue and ultraviolet (UV) light transilluminators. As a proof-of-concept, reliable multiplex RAVI-CRISPR detection of genome-edited pigs was demonstrated, exhibiting 100% sensitivity and specificity for the analysis of CD163 knockout, lactoferrin (LF) knock-in, and wild-type pig samples. This portable naked-eye multiplex RAVI-CRISPR detection platform can provide accurate point-of-care screening of genetically modified animals and infectious diseases in resource-limited settings.

Using Ground and UAV Vegetation Indexes for the Selection of Fungal-Resistant Bread Wheat Varieties

The productivity of wheat in the Mediterranean region is under threat due to climate-change-related environmental factors, including fungal diseases that can negatively impact wheat yield and quality. Wheat phenotyping tools utilizing affordable, high-throughput plant phenotyping (HTPP) techniques, such as aerial and ground RGB images and quick canopy and leaf sensors, can aid in assessing crop status and selecting tolerant wheat varieties. This study focused on the impact of fungal diseases on wheat productivity in the Mediterranean region, considering the need for a precise selection of tolerant wheat varieties. This research examined the use of affordable HTPP methods, including imaging and active multispectral sensors, to aid in crop management for improved wheat health and to support commercial field phenotyping programs. This study evaluated 40 advanced lines of bread wheat (Triticum aestivum L.) at five locations across northern Spain, comparing fungicide-treated and untreated blocks under fungal disease pressure (Septoria, brown rust, and stripe rust observed). Measurements of leaf-level pigments and canopy vegetation indexes were taken using portable sensors, field cameras, and imaging sensors mounted on unmanned aerial vehicles (UAVs). Significant differences were observed in Dualex flavonoids and the nitrogen balance index (NBI) between treatments in some locations (p &lt; 0.001 between Elorz and Ejea). Measurements of canopy vigor and color at the plot level showed significant differences between treatments at all sites, highlighting indexes such as the green area (GA), crop senescence index (CSI), and triangular greenness index (TGI) in assessing the effects of fungicide treatments on different wheat cultivars. RGB vegetation indexes from the ground and UAV were highly correlated (r = 0.817 and r = 0.810 for TGI and NGRDI). However, the Greenseeker NDVI sensor was found to be more effective in estimating grain yield and protein content (R2 = 0.61–0.7 and R2 = 0.45–0.55, respectively) compared to the aerial AgroCam GEO NDVI (R2 = 0.25–0.35 and R2 = 0.12–0.21, respectively). We suggest as a practical consideration the use of the GreenSeeker NDVI as more user-friendly and less affected by external environmental factors. This study emphasized the throughput benefits of RGB UAV HTPPs with the high similarity between ground and aerial results and highlighted the potential for HTPPs in supporting the selection of fungal-disease-resistant bread wheat varieties.

Measurements of the lateral cerebellar hemispheres using near-infrared spectroscopy through comparison between autism spectrum disorder and typical development

The cerebellum plays a vital role in cognition, communication with the cerebral cortex, and fine motor coordination. Near-infrared spectroscopy (NIRS) is a portable, less restrictive, and noninvasive functional brain imaging method that can capture brain activity during movements by measuring the relative oxyhemoglobin (oxy-Hb) concentrations in the blood. However, the feasibility of using NIRS to measure cerebellar activity requires discussion. We compared NIRS responses between areas assumed to be the cerebellum and the occipital lobe during a fine motor task (tying a bow knot) and a visual task. Our results showed that the oxy-Hb concentration increased more in the occipital lobe than in the cerebellum during the visual task (p =.034). In contrast, during the fine motor task, the oxy-Hb concentration decreased in the occipital lobe but increased significantly in the cerebellum, indicating a notable difference (p =.015). These findings suggest that we successfully captured cerebellar activity associated with processing, particularly fine motor coordination. Moreover, the observed responses did not differ between individuals with autism spectrum disorder and those with typical development. Our study demonstrates the meaningful utility of NIRS as a method for measuring cerebellar activity during movements.

Low-field magnetic resonance imaging in a boy with intracranial bolt after severe traumatic brain injury: illustrative case.

Conventional magnetic resonance imaging (cMRI) is sensitive to motion and ferromagnetic material, leading to suboptimal images and image artifacts. In many patients with neurological injuries, an intracranial bolt (ICB) is placed for monitoring intracranial pressure (ICP). Repeated imaging (computed tomography [CT] or cMRI) is frequently required to guide management. A low-field (0.064-T) portable magnetic resonance imaging (pMRI) machine may provide images in situations that were previously considered contraindications for cMRI. A 10-year-old boy with severe traumatic brain injury was admitted to the pediatric intensive care unit, and an ICB was placed. Initial head CT showed a left-sided intraparenchymal hemorrhage with intraventricular dissection and cerebral edema with mass effect. Repeated imaging was required to assess the brain structure because of continually fluctuating ICP. Transferring the patient to the radiology suite was risky because of his critical condition and the presence of an ICB; hence, pMRI was performed at the bedside. Images obtained were of excellent quality without any ICB artifact, guiding the decision to continue to manage the patient conservatively. The child later improved and was discharged from the hospital. pMRI can be used to obtain excellent images at the bedside in patients with an ICB, providing useful information for better management of patients with neurological injuries.

Deep Belief Networks (DBN) with IoT-Based Alzheimer’s Disease Detection and Classification

Dementias that develop in older people test the limits of modern medicine. As far as dementia in older people goes, Alzheimer’s disease (AD) is by far the most prevalent form. For over fifty years, medical and exclusion criteria were used to diagnose AD, with an accuracy of only 85 per cent. This did not allow for a correct diagnosis, which could be validated only through postmortem examination. Diagnosis of AD can be sped up, and the course of the disease can be predicted by applying machine learning (ML) techniques to Magnetic Resonance Imaging (MRI) techniques. Dementia in specific seniors could be predicted using data from AD screenings and ML classifiers. Classifier performance for AD subjects can be enhanced by including demographic information from the MRI and the patient’s preexisting conditions. In this article, we have used the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In addition, we proposed a framework for the AD/non-AD classification of dementia patients using longitudinal brain MRI features and Deep Belief Network (DBN) trained with the Mayfly Optimization Algorithm (MOA). An IoT-enabled portable MR imaging device is used to capture real-time patient MR images and identify anomalies in MRI scans to detect and classify AD. Our experiments validate that the predictive power of all models is greatly enhanced by including early information about comorbidities and medication characteristics. The random forest model outclasses other models in terms of precision. This research is the first to examine how AD forecasting can benefit from using multimodal time-series data. The ability to distinguish between healthy and diseased patients is demonstrated by the DBN-MOA accuracy of 97.456%, f-Score of 93.187 %, recall of 95.789 % and precision of 94.621% achieved by the proposed technique. The experimental results of this research demonstrate the efficacy, superiority, and applicability of the DBN-MOA algorithm developed for the purpose of AD diagnosis.

A Tactile Skin System for Touch Sensing with Ultrasound Tomography.

The tomographic imaging method is promising in large-area touch-sensing applications. This paper presents a new type of such touch sensor using ultrasonic tomography (UST) via sound attenuation imaging. UST is gaining popularity as a portable, fast, and inexpensive imaging system for medical and industrial applications. UST can be developed in different operation modes. A transmission mode UST is being investigated as a force- and touch-sensitive skin. A prototype skin sensor was developed in a 200 mm diameter circular UST array containing two sets of 16 transducers, with one operating at a central frequency of 40 kHz and the other at 300 kHz. The extension of the sensor in terms of dimension, up to 400 mm diameter, and number of sensors, up to 32 transducers, is possible where eight points of contact were reconstructed successfully. The medium contains a 20 mm high water region, and a soft silicone membrane covers the liquid region. When touchpoints or forces are applied to the soft skin of the membrane, the sound pathway is disrupted, resulting in an image of the touch position and touch force intensity using a tomographic UST algorithm. Several static and dynamic experiments are conducted to demonstrate this novel application of UST. In addition, a correlation analysis is carried out to establish the force quantification potential for the UST-based tactile skin.

Correction to: Identification of White Matter Hyperintensities in Routine Emergency Department Visits Using Portable Bedside Magnetic Resonance Imaging.

Correction to: Identification of White Matter Hyperintensities in Routine Emergency Department Visits Using Portable Bedside Magnetic Resonance Imaging.

IMPI: portable human-sized magnetic particle imaging scanner for real-time endovascular interventions

Minimally invasive endovascular interventions have become an important tool for the treatment of cardiovascular diseases such as ischemic heart disease, peripheral artery disease, and stroke. X-ray fluoroscopy and digital subtraction angiography are used to precisely guide these procedures, but they are associated with radiation exposure for patients and clinical staff. Magnetic Particle Imaging (MPI) is an emerging imaging technology using time-varying magnetic fields combined with magnetic nanoparticle tracers for fast and highly sensitive imaging. In recent years, basic experiments have shown that MPI has great potential for cardiovascular applications. However, commercially available MPI scanners were too large and expensive and had a small field of view (FOV) designed for rodents, which limited further translational research. The first human-sized MPI scanner designed specifically for brain imaging showed promising results but had limitations in gradient strength, acquisition time and portability. Here, we present a portable interventional MPI (iMPI) system dedicated for real-time endovascular interventions free of ionizing radiation. It uses a novel field generator approach with a very large FOV and an application-oriented open design enabling hybrid approaches with conventional X-ray-based angiography. The feasibility of a real-time iMPI-guided percutaneous transluminal angioplasty (PTA) is shown in a realistic dynamic human-sized leg model.

A transceiver integrated piezoelectric micromachined ultrasound transducer array for underwater imaging

In this article, a scandium-doped aluminum nitride (Sc0.2Al0.8N) piezoelectric micromachined ultrasound transducer (PMUT) array for underwater imaging is presented. The reported PMUT array integrates a transmitter and a receiver in one transduction cell, in which the outer top electrode is used for transmitting while the inner top electrode is employed for simultaneously receiving ultrasonic waves, respectively. A 7 × 8 transduction cell array with characteristic size of 500μm is designed in a bioinspired honeycomb architecture and developed based on a piezoelectric on silicon-on-insulator (SOI) platform. The top electrode of the transduction cell is split into the outer and inner sections with the optimized size ratio for achieving transceiver integration in one cell. The fabricated PMUT array exhibits a transmit sensitivity of 146.59 dB (re: 1 μPa/V), and a receive sensitivity of −173.70 dB (re: 1 V/μPa) at its resonant frequency of around 150 kHz in water. In order to demonstrate the feasibility of underwater imaging, the PMUT array and its signal conditional circuits are packaged using an acoustically transparent material. Ultrasonic pulse-echo imaging with the developed PMUT array is demonstrated without implementation of a switching circuit to separate the transmit and reflected signals, due to the transceiver integration approach proposed in our work. This work demonstrates the feasibility of underwater imaging for the transceiver integrated PMUT array, which has great commercial value for minimized and portable underwater imaging.

Non-Invasive Mapping of Cerebral Autoregulation Using Near-Infrared Spectroscopy: A Study Protocol.

The ability of cerebral vessels to maintain a fairly constant cerebral blood flow is referred to as cerebral autoregulation (CA). Using near-infrared spectroscopy (NIRS) paired with arterial blood pressure (ABP) monitoring, continuous CA can be assessed non-invasively. Recent advances in NIRS technology can help improve the understanding of continuously assessed CA in humans with high spatial and temporal resolutions. We describe a study protocol for creating a new wearable and portable imaging system that derives CA maps of the entire brain with high sampling rates at each point. The first objective is to evaluate the CA mapping system's performance during various perturbations using a block-trial design in 50 healthy volunteers. The second objective is to explore the impact of age and sex on regional disparities in CA using static recording and perturbation testing in 200 healthy volunteers. Using entirely non-invasive NIRS and ABP systems, we hope to prove the feasibility of deriving CA maps of the entire brain with high spatial and temporal resolutions. The development of this imaging system could potentially revolutionize the way we monitor brain physiology in humans since it would allow for an entirely non-invasive continuous assessment of regional differences in CA and improve our understanding of the impact of the aging process on cerebral vessel function.

A portable electrochemiluminescence imaging system based on image processing for real-time detection of melamine

In this study, a portable electrochemiluminescence (ECL) imaging system based on Raspberry Pi was developed for the instant detection of melamine. The system employed a lithium battery as the excitation source and Ru(bpy)32+/TPA as the reaction system. A homemade 3D-printed black box served as a reaction chamber for the ECL reaction. ECL images were captured by a camera and subsequently classified by the MobileNet model. Over 500 images obtained from the experiment were used as a self-built dataset to train the neural network model. As the core processor, Raspberry Pi was not only used to control the camera, but also to perform Image enhancement and color analysis. The experimental results were further validated using image processing algorithms. The system demonstrated highly sensitive detection of melamine under optimal conditions, with a linear fit curve in the range of 10−8–10−3 M and a detection limit of 3.54 nM. In conclusion, this system holds great potential for the instant detection of melamine.

Evaluation of a portable retinal imaging device: towards a comparative quantitative analysis for morphological measurements of retinal blood vessels.

This study investigated the possibility of using low-cost, handheld, retinal imaging devices for the automatic extraction of quantifiable measures of retinal blood vessels. Initially, the available handheld devices were compared using a Zeiss model eye incorporating a USAF resolution test chart to assess their optical properties. The only suitable camera of the five evaluated was the Horus DEC 200. This device was then subjected to a detailed evaluation in which images in human eyes taken from the handheld camera were compared in a quantitative analysis with those of the same eye from a Canon CR-DGi retinal desktop camera. We found that the Horus DEC 200 exhibited shortcomings in capturing images of human eyes by comparison with the Canon. More images were rejected as being unevaluable or suffering failures in automatic segmentation than with the Canon, and even after exclusion of affected images, the Horus yielded lower measurements of vessel density than the Canon. A number of issues affecting handheld cameras in general and some features of the Horus in particular have been identified that might contribute to the observed differences in performance. Some potential mitigations are discussed which might yield improvements in performance, thus potentially facilitating use of handheld retinal imaging devices for quantitative retinal microvascular measurements.