A novel deep learning technique for medical image analysis using improved optimizer.

Application of Convolutional neural network in spectrum of Medical image analysis are providing benchmark outputs which converges the interest of many researchers to explore it in depth. Latest preprocessing technique Real ESRGAN (Enhanced super resolution generative adversarial network) and GFPGAN (Generative facial prior GAN) are proving their efficacy in providing high resolution dataset. Objective: Optimizer plays a vital role in upgrading the functioning of CNN model. Different optimizers like Gradient descent, Stochastic Gradient descent, Adagrad, Adadelta and Adam etc. are used for classification and segmentation of Medical image but they suffer from slow processing due to their large memory requirement. Stochastic Gradient descent suffers from high variance and is computationally expensive. Dead neuron problem also proves to detrimental to the performance of most of the optimizers. A new optimization technique Gradient Centralization is providing the unparalleled result in terms of generalization and execution time. Method: Our paper explores the next factor which is the employment of new optimization technique, Gradient centralization (GC) to our integrated framework (Model with advanced preprocessing technique). Result and conclusion: Integrated Framework of Real ESRGAN and GFPGAN with Gradient centralization provides an optimal solution for deep learning models in terms of Execution time and Loss factor improvement.

The realization of medical devices for precision surgery - development and implementation of 'stop-and-go' imaging technologies.

INTRODUCTION: Surgery and biomedical imaging encompass a big share of the medical-device market. The ever-mounting demand for precision surgery has driven the integration of these two into the field of image-guided surgery. A key-question herein is how imaging modalities can guide the surgical decision-making process. Through performance-based design, chemists, engineers, and doctors need to build a bridge between imaging technologies and surgical challenges. AREAS-COVERED: This perspective article highlights the complementary nature between the technological design of an image-guidance modality and the type of procedure performed. The specific roles of the involved professionals, imaging technologies, and surgical indications are addressed. EXPERT-OPINION: Molecular-image-guided surgery has the potential to advance pre-, intra- and post-operative tissue characterization. To achieve this, surgeons need the access to well-designed indication-specific chemical-agents and detection modalities. Hereby, some technologies stimulate exploration ('go'), while others stimulate caution ('stop'). However, failing to adequately address the indication-specific needs rises the risk of incorrect tool employment and sub-optimal surgical performance. Therefore, besides the availability of new technologies, market growth is highly dependent on the practical nature and impact on real-life clinical care. While urology currently takes the lead in the widespread implementation of image-guidance technologies, the topic is generic and its popularity spreads rapidly within surgical oncology.

Integrated lithium niobate microwave photonic processing engine.

Integrated microwave photonics (MWP) is an intriguing technology for the generation, transmission and manipulation of microwave signals in chip-scale optical systems1,2. In particular, ultrafast processing of analogue signals in the optical domain with high fidelity and low latency could enable a variety of applications such as MWP filters3-5, microwave signal processing6-9 and image recognition10,11. An ideal integrated MWP processing platform should have both an efficient and high-speed electro-optic modulation block to faithfully perform microwave-optic conversion at low power and also a low-loss functional photonic network to implement various signal-processing tasks. Moreover, large-scale, low-cost manufacturability is required to monolithically integrate the two building blocks on the same chip. Here we demonstrate such an integrated MWP processing engine based on a 4 inch wafer-scale thin-film lithium niobate platform. It can perform multipurpose tasks with processing bandwidths of up to 67 GHz at complementary metal-oxide-semiconductor (CMOS)-compatible voltages. We achieve ultrafast analogue computation, namely temporal integration and differentiation, at sampling rates of up to 256 giga samples per second, and deploy these functions to showcase three proof-of-concept applications: solving ordinary differential equations, generating ultra-wideband signals and detecting edges in images. We further leverage the image edge detector to realize a photonic-assisted image segmentation model that can effectively outline the boundaries of melanoma lesion in medical diagnostic images. Our ultrafast lithium niobate MWP engine could provide compact, low-latency and cost-effective solutions for future wireless communications, high-resolution radar and photonic artificial intelligence.

Construcción y validación de un fantoma torácico pediátrico asequible para optimizar la dosis / Low-cost chest paediatric phantom for dose optimisation: construction and validation

Introducción y objetivosPara llevar a cabo estudios de optimización de dosis, el fantoma de imagenología debe ser adecuado para evaluar la calidad de la imagen. El coste de los fantomas de gama alta suele ser prohibitivo, por lo que es necesario hallar un método de construcción asequible que emplee sustitutos tisulares que sean razonablemente fáciles de obtener.Materiales y métodosSe realizaron cálculos teóricos de las características radiológicas de cada uno de los pulmones, el hueso cortical y los tejidos blandos con el fin de elegir el sustituto adecuado; para ello, se eligieron el corcho, el cloruro de polivinilo (PVC) y el agua, respectivamente. La validación consistió, en primer lugar, en la medición de las unidades Hounsfield (UH) de tomografía computarizada (TC) de los tejidos de un paciente real y su posterior comparación con las anatomías correspondientes en el fantoma construido. En segundo lugar, se obtuvieron los valores de relación señal/ruido (S/R) y de relación contraste/ruido (C/R) para evaluar la calidad de las imágenes generadas a partir del fantoma construido y comparar sus tendencias con un fantoma válido utilizando diferentes parámetros de exposición (valores pico de kilovoltaje [kVp] y miliamperios por segundo [mAs]).ResultadosPartiendo de los cálculos teóricos, las diferencias porcentuales exhibieron una precisión elevada en los sustitutos tisulares al simular los tejidos de un paciente real; con PVC fue de ≥ 5,78%, con corcho ≥ 4,46% y con agua ≥ 5%. La diferencia porcentual (UH de TC) entre el pulmón y el hueso cortical y sus sustitutos tisulares equivalentes fue de 10,44% y de 0,53 a 3,17%, respectivamente. Se encontraron fuertes correlaciones positivas para la S/R al variar tanto los valores de kVp (0,79) como de mAs (0,65). Por el contrario, se halló que la fuerza de correlación de los valores de la C/R era moderada al cambiar los valores de kVp (0,58) y mAs (0,53).(AU)

Introduction and ObjectivesIn order to perform chest dose optimisation studies, the imaging phantom should be adequate for image quality evaluation. Since high-end phantoms are cost prohibitive, there is a need for a low-cost construction method with fairly available tissue substitutes.Materials and MethodsTheoretical calculations of radiological characteristics were performed for each of lung, cortical bone and soft tissues in order to choose appropriate substitute, then, cork, P.V.C. (Polyvinyl Chloride) and water were chosen, respectively. Validation included, firstly, measuring CT Hounsfield Units (HU) of a real patient's tissues then compared against their corresponding anatomies in the constructed phantom. Secondly, Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values were acquired in this study to evaluate the quality of images generated from the constructed phantom, then, compare their trends with a valid phantom under different exposure parameters (kVp and mAs).ResultsFrom theoretical calculations, the percentage differences showed high accuracy of tissue substitutes when simulating real patient tissues; P.V.C. was ≥ 5.78%, cork was ≥ 4.46% and water ≥ 5%. The percentage difference (CT HU) between lung and cortical bone and their equivalent tissue substitutes were 10.44% and 0.53%-3.17%, respectively. Strong positive correlations were found for SNR when changing both kVp (0.79) and mAs (0.65). While the correlation strength of CNR values were found to be moderate when changing both kVp (0.58) and mAs (0.53).ConclusionsOur low-cost phantom approved through CT HU that their materials replicate the radiological characteristics of real one-year-old child while SNR and SNR correlations confirmed its applicability in imaging and optimisation studies.(AU)

National inventory of authorized diagnostic imaging equipment in Ghana: data as of September 2020.

Introduction: to address the challenge of inadequate and non-equitable distribution of diagnostic imaging equipment, countries are encouraged to evaluate the distribution of installed systems and undertake adequate monitoring to ensure equitability. Ghana´s medical imaging resources have been analyzed in this study and evaluated against the status in other countries. Methods: data on registered medical imaging equipment were retrieved from the database of the Nuclear Regulatory Authority and analyzed. The equipment/population ratio was mapped out graphically for the 16 regions of Ghana. Comparison of the equipment/population ratio was made with the situation in other countries. Results: six hundred and seventy-four diagnostic imaging equipment units from 266 medical imaging facilities (2.5 units/facility), comprising computed tomography (CT), general X-ray, dental X-ray, single-photon emission computed tomography (SPECT) gamma camera, fluoroscopy, mammography and magnetic resonance imaging (MRI) were surveyed nationally. None of the imaging systems measured above the Organization for Economic Co-operation and Development (OECD) average imaging units per million populations (u/mp). The overall equipment/population ratio estimated nationally was 21.4 u/mp. Majority of the imaging systems were general X-ray, installed in the Greater Accra and Ashanti regions. The regional estimates of equipment/population ratios were Greater Accra (49.6 u/mp), Ashanti (22.4 u/mp), Western (21.4 u/mp), Eastern (20.6 u/mp), Bono East (20.0 u/mp), Bono (19.2 u/mp), Volta (17.9 u/mp), Upper West (16.7 u/mp), Oti (12.5 u/mp), Central (11.9 u/mp), Northern (8.9 u/mp), Ahafo (8.9 u/mp), Upper East (6.9 u/mp), Western North (6.7 u/mp), Savannah (5.5 u/mp) and North-East (1.7 u/mp). Conclusion: medical imaging equipment shortfall exist across all imaging modalities in Ghana. A wide inter-regional disparity in the distribution of medical imaging equipment exists contrary to WHO´s recommendation for equitable distribution. A concerted national plan will be needed to address the disparity.

Impact of dental cone-beam computed tomography on diagnostic evaluation and treatment plan for the maxillary sinus in dental implant planning / Impacto de la tomografía computarizada de haz cónico en el diagnóstico y plan detratamiento preimplantologico de senos maxilares

Objective: To determine the impact of CBCT on diagnostic evaluation and treatment plan for the maxillary sinus in dental implant planning. Material and Methods: Diagnostic evaluation and treatment plan for the maxillary sinus were evaluated by eight specialists experienced in dental implant placement. Eight panoramic radiographs (PAN) and CBCT examinations were obtained from five adult patients with a specific clinical need for dental implants. Evaluation was performed first on PAN then, at least 2 weeks later, on CBCT. Residual alveolar ridge height, mucosal thickening, radiographic findings and treatment plan were recorded. The confidence level was evaluated for both diagnostic evaluation and treatment plan. The kappa statistic for intra-observer reproducibility and McNemar test were performed. Results: In the diagnostic evaluation, CBCT showed significant impact on the diagnosis of radiographic findings. Availability of CBCT significantly changed the treatment plan, for less invasive treatment, or no treatment need. Observers had significantly greater confidence when using CBCT than PAN, when indicating presence of mucosal thickening and radiographic findings in the maxillary sinus. In addition, CBCT increased confidence in the treatment plan. Conclusion: The present study suggests that CBCT has an impact on the diagnostic evaluation of radiographic findings in the maxillary sinus and on the decision to place implants, owing to misdiagnosis of pathology and planning of more invasive treatments when using PAN. Availability of CBCT also improves clinician confidence. Further studies at higher levels of diagnostic efficacy should be performed, to justify the use of CBCT, by evaluating the actual treatment performed and its outcome.

Objetivo: Determinar el impacto de la tomografía computarizada de haz cónico (CBCT) en la evaluación diagnóstica y el plan de tratamiento del seno maxilar en la planificación de implantes dentales. Material y Métodos: La evaluación diagnóstica y el plan de tratamiento del seno maxilar fueron evaluados por ocho especialistas con experiencia en la colocación de implantes dentales. Se obtuvieron ocho radiografías panorámicas (PAN) y exámenes CBCT de cinco pacientes adultos con una necesidad clínica específica de implantes dentales. La evaluación se realizó primero en PAN y luego, al menos dos semanas después, en CBCT. Se registraron la altura del reborde alveolar residual, el engrosamiento de la mucosa, los hallazgos radiográficos y el plan de tratamiento. Se evaluó el nivel de confianza tanto para la evaluación diagnóstica como para el plan de tratamiento. Se realizó el estadístico kappa para la reproducibilidad intraobservador y la prueba de McNemar. Resultados: En la evaluación diagnóstica, CBCT mostró un impacto significativo en el diagnóstico de los hallazgos radiográficos. La disponibilidad de CBCT cambió significativamente el plan de tratamiento, para un tratamiento menos invasivo o sin necesidad de tratamiento. Los observadores tuvieron una confianza significativamente mayor al usar CBCT que PAN, al indicar la presencia de engrosamiento de la mucosa y hallazgos radiográficos en el seno maxilar. Además, CBCT aumentó la confianza en el plan de tratamiento. Conclusión: El presente estudio sugiere que la CBCT tiene un impacto en la evaluación diagnóstica de los hallazgos radiográficos en el seno maxilar y en la decisión de colocar implantes, debido al diagnóstico erróneo de la patología y la planificación de tratamientos más invasivos al usar PAN. La disponibilidad de CBCT también mejora la confianza del clínico. Se deben realizar más estudios a niveles más altos de eficacia diagnóstica para justificar el uso de CBCT, evaluando el tratamiento real realizado y su resultado.

An Overview on Bipolar Junction Transistor as a Sensor for X-ray Beams Used in Medical Diagnosis.

Although not manufactured to be used under X-ray photons, the commercial bipolar junction transistor (BJT) is an electronic device that can be used as an ionizing radiation sensor. In this article an overview on the BJT and its principle of operation were made for the purpose of better understanding how such a semiconductor device behaves when under diagnostic X-ray beam. Therefore, it addresses some topics such as the structure of the device, the bias configuration when operating in active mode, and so on. Even knowing that the most complete theory to describe the "transistor effect" is based on quantum theory (the energy band theory of solids), here it is preferable to take a simpler experimental approach to clearly understand the operation of the BJT. In electronics, the BJT is used as a current amplifier, and depending on the bias and point of view it also becomes a voltage amplifier. In the analysis of BJT under an X-ray beam, in addition to its operation as a sensor to measure the dose or some diagnostic X-ray tube parameter, it has also led to technological innovation in the technique of digital data storage based on the effect of radiation.

Spatial transcriptomics using combinatorial fluorescence spectral and lifetime encoding, imaging and analysis.

Multiplexed mRNA profiling in the spatial context provides new information enabling basic research and clinical applications. Unfortunately, existing spatial transcriptomics methods are limited due to either low multiplexing or complexity. Here, we introduce a spatialomics technology, termed Multi Omic Single-scan Assay with Integrated Combinatorial Analysis (MOSAICA), that integrates in situ labeling of mRNA and protein markers in cells or tissues with combinatorial fluorescence spectral and lifetime encoded probes, spectral and time-resolved fluorescence imaging, and machine learning-based decoding. We demonstrate MOSAICA's multiplexing scalability in detecting 10-plex targets in fixed colorectal cancer cells using combinatorial labeling of five fluorophores with facile error-detection and removal of autofluorescence. MOSAICA's analysis is strongly correlated with sequencing data (Pearson's r = 0.96) and was further benchmarked using RNAscopeTM and LGC StellarisTM. We further apply MOSAICA for multiplexed analysis of clinical melanoma Formalin-Fixed Paraffin-Embedded (FFPE) tissues. We finally demonstrate simultaneous co-detection of protein and mRNA in cancer cells.

Improved clearing method contributes to deep imaging of plant organs.

Tissue clearing methods are increasingly essential for the microscopic observation of internal tissues of thick biological organs. We previously developed TOMEI, a clearing method for plant tissues; however, it could not entirely remove chlorophylls nor reduce the fluorescent signal of fluorescent proteins. Here, we developed an improved TOMEI method (iTOMEI) to overcome these limitations. First, a caprylyl sulfobetaine was determined to efficiently remove chlorophylls from Arabidopsis thaliana seedlings without GFP quenching. Next, a weak alkaline solution restored GFP fluorescence, which was mainly lost during fixation, and an iohexol solution with a high refractive index increased sample transparency. These procedures were integrated to form iTOMEI. iTOMEI enables the detection of much brighter fluorescence than previous methods in tissues of A. thaliana, Oryza sativa, and Marchantia polymorpha. Moreover, a mouse brain was also efficiently cleared by the iTOMEI-Brain method within 48 h, and strong fluorescent signals were detected in the cleared brain.

Portable, handheld, and affordable blood perfusion imager for screening of subsurface cancer in resource-limited settings.

Precise information on localized variations in blood circulation holds the key for noninvasive diagnostics and therapeutic assessment of various forms of cancer. While thermal imaging by itself may provide significant insights on the combined implications of the relevant physiological parameters, viz. local blood perfusion and metabolic balance due to active tumors as well as the ambient conditions, knowledge of the tissue surface temperature alone may be somewhat inadequate in distinguishing between some ambiguous manifestations of precancer and cancerous lesions, resulting in compromise of the selectivity in detection. This, along with the lack of availability of a user-friendly and inexpensive portable device for thermal-image acquisition, blood perfusion mapping, and data integration acts as a deterrent against the emergence of an inexpensive, contact-free, and accurate in situ screening and diagnostic approach for cancer detection and management. Circumventing these constraints, here we report a portable noninvasive blood perfusion imager augmented with machine learning-based quantitative analytics for screening precancerous and cancerous traits in oral lesions, by probing the localized alterations in microcirculation. With a proven overall sensitivity >96.66% and specificity of 100% as compared to gold-standard biopsy-based tests, the method successfully classified oral cancer and precancer in a resource-limited clinical setting in a double-blinded patient trial and exhibited favorable predictive capabilities considering other complementary modes of medical image analysis as well. The method holds further potential to achieve contrast-free, accurate, and low-cost diagnosis of abnormal microvascular physiology and other clinically vulnerable conditions, when interpreted along with complementary clinically evidenced decision-making perspectives.

Quantum magnetic imaging of iron organelles within the pigeon cochlea.

The ability of pigeons to sense geomagnetic fields has been conclusively established despite a notable lack of determination of the underlying biophysical mechanisms. Quasi-spherical iron organelles previously termed "cuticulosomes" in the cochlea of pigeons have potential relevance to magnetoreception due to their location and iron composition; however, data regarding the magnetic susceptibility of these structures are currently limited. Here quantum magnetic imaging techniques are applied to characterize the magnetic properties of individual iron cuticulosomes in situ. The stray magnetic fields emanating from cuticulosomes are mapped and compared to a detailed analytical model to provide an estimate of the magnetic susceptibility of the individual particles. The images reveal the presence of superparamagnetic and ferrimagnetic domains within individual cuticulosomes and magnetic susceptibilities within the range 0.029 to 0.22. These results provide insights into the elusive physiological roles of cuticulosomes. The susceptibilities measured are not consistent with a torque-based model of magnetoreception, placing iron storage and stereocilia stabilization as the two leading putative cuticulosome functions. This work establishes quantum magnetic imaging as an important tool to complement the existing array of techniques used to screen for potential magnetic particle-based magnetoreceptor candidates.

Optimization of retina-like illumination patterns in ghost imaging.

Ghost imaging (GI) reconstructs images using a single-pixel or bucket detector, which has the advantages of scattering robustness, wide spectrum, and beyond-visual-field imaging. However, this technique needs large amounts of measurements to obtain a sharp image. Numerous methods are proposed to overcome this disadvantage. Retina-like patterns, as one of the compressive sensing approaches, enhance the imaging quality of the region of interest (ROI) while maintaining measurements. The design of the retina-like patterns determines the performance of the ROI in the reconstructed image. Unlike the conventional method to fill in ROI with random patterns, optimizing retina-like patterns by filling in the ROI with the patterns containing the sparsity prior of objects is proposed. The proposed method is then verified by simulations and experiments compared with conventional GI, retina-like GI, and GI using patterns optimized by principal component analysis. The method using optimized retina-like patterns obtains the best imaging quality in ROI among other methods. Meanwhile, the good generalization capability of the optimized retina-like pattern is also verified. The feature information of the target can be obtained while designing the size and position of the ROI of retina-like patterns to optimize the ROI pattern. The proposed method facilitates the realization of high-quality GI.

Noise robustness of persistent homology on greyscale images, across filtrations and signatures.

Topological data analysis is a recent and fast growing field that approaches the analysis of datasets using techniques from (algebraic) topology. Its main tool, persistent homology (PH), has seen a notable increase in applications in the last decade. Often cited as the most favourable property of PH and the main reason for practical success are the stability theorems that give theoretical results about noise robustness, since real data is typically contaminated with noise or measurement errors. However, little attention has been paid to what these stability theorems mean in practice. To gain some insight into this question, we evaluate the noise robustness of PH on the MNIST dataset of greyscale images. More precisely, we investigate to what extent PH changes under typical forms of image noise, and quantify the loss of performance in classifying the MNIST handwritten digits when noise is added to the data. The results show that the sensitivity to noise of PH is influenced by the choice of filtrations and persistence signatures (respectively the input and output of PH), and in particular, that PH features are often not robust to noise in a classification task.

Intraoral scanners for capturing the palate and its relation to the dentition.

Proper superimposition of intraoral scan generated 3D models enables detailed assessment of soft and hard tissue surface changes. This requires accurate 3D models and stable structures as superimposition references. In the maxilla, different reference areas have been proposed, mostly located at the palatal region. In this in vivo study we evaluated the precision of two intraoral scanners (TRIOS 3, 3Shape and CS 3600, Carestream) at the maxilla, focusing on the palate itself and also on its spatial relation to the dentition, following palatal superimposition. Precision was tested through the superimposition of repeated scans on the palate and the dental arch. Overall, the median precision of both scanners was high (< 0.1 mm). Scanner precision was comparable when the palatal area was tested individually. However, TRIOS 3 showed higher precision regarding the assessment of the dental arch, following superimposition of repeated models on the palate (median difference: approximately 40 µm). In few cases, local areas of higher imprecision were present for both scanners, exceeding 0.3 mm. Thus, scanner precision seems to be high in small, but slightly reduced considering larger areas, with differences between scanners. However, the effect on individual tooth position relative to the palate was for both scanners limited.

Development of a smartphone-based lateral-flow imaging system using machine-learning classifiers for detection of Salmonella spp.

Salmonella spp. are a foodborne pathogen frequently found in raw meat, egg products, and milk. Salmonella is responsible for numerous outbreaks, becoming a frequent major public-health concern. Many studies have recently reported handheld and rapid devices for microbial detection. This study explored a smartphone-based lateral-flow assay analyzer which employed machine-learning algorithms to detect various concentrations of Salmonella spp. from the test line images. When cell numbers are low, a faint test line is difficult to detect, leading to misleading results. Hence, this study focused on the development of a smartphone-based lateral-flow assay (SLFA) to distinguish ambiguous concentrations of test line with higher confidence. A smartphone cradle was designed with an angled slot to maximize the intensity, and the optimal direction of the optimal incident light was found. Furthermore, the combination of color spaces and the machine-learning algorithms were applied to the SLFA for classifications. It was found that the combination of L*a*b and RGB color space with SVM and KNN classifiers achieved the high accuracy (95.56%). A blind test was conducted to evaluate the performance of devices; the results by machine-learning techniques reported less error than visual inspection. The smartphone-based lateral-flow assay provided accurate interpretation with a detection limit of 5 × 104 CFU/mL commercially available lateral-flow assays.

CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance.

Most oncological cases can be detected by imaging techniques, but diagnosis is based on pathological assessment of tissue samples. In recent years, the pathology field has evolved to a digital era where tissue samples are digitised and evaluated on screen. As a result, digital pathology opened up many research opportunities, allowing the development of more advanced image processing techniques, as well as artificial intelligence (AI) methodologies. Nevertheless, despite colorectal cancer (CRC) being the second deadliest cancer type worldwide, with increasing incidence rates, the application of AI for CRC diagnosis, particularly on whole-slide images (WSI), is still a young field. In this review, we analyse some relevant works published on this particular task and highlight the limitations that hinder the application of these works in clinical practice. We also empirically investigate the feasibility of using weakly annotated datasets to support the development of computer-aided diagnosis systems for CRC from WSI. Our study underscores the need for large datasets in this field and the use of an appropriate learning methodology to gain the most benefit from partially annotated datasets. The CRC WSI dataset used in this study, containing 1,133 colorectal biopsy and polypectomy samples, is available upon reasonable request.

Clinical Role of Smartphone Fundus Imaging in Diabetic Retinopathy and Other Neuro-retinal Diseases.

Purpose: In today's life, many electronic gadgets have the potential to become invaluable health care devices in future. The gadgets in this category include smartphones, smartwatches, and others. Till now, smartphone role has been highlighted on many occasions in different areas, and they continue to possess immense role in clinical documentation, clinical consultation, and digitalization of ocular care. In last one decade, many treatable conditions including diabetic retinopathy, glaucoma, and other pediatric retinal diseases are being imaged using smartphones.Methods: To comprehend this cumulative knowledge, a detailed medical literature search was conducted on PubMed/Medline, Scopus, and Web of Science till February 2021.Results: The included literature revealed a definitive progress in posterior segment imaging. From simple torch light with smartphone examination to present day compact handy devices with artificial intelligence integrated software's have changed the very perspectives of ocular imaging in ophthalmology. The consistently reproducible results, constantly improving imaging techniques, and most importantly their affordable costs have renegotiated their role as effective screening devices in ophthalmology. Moreover, the obtained field of view, ocular safety, and their key utility in non-ophthalmic specialties are also growing.Conclusions: To conclude, smartphone imaging can now be considered as a quick, cost-effective, and digitalized tool for posterior segment screenings, however, their definite role in routine ophthalmic clinics is yet to be established.

Avalanche photodetectors with photon trapping structures for biomedical imaging applications.

Enhancing photon detection efficiency and time resolution in photodetectors in the entire visible range is critical to improve the image quality of time-of-flight (TOF)-based imaging systems and fluorescence lifetime imaging (FLIM). In this work, we evaluate the gain, detection efficiency, and timing performance of avalanche photodiodes (APD) with photon trapping nanostructures for photons with 450 nm and 850 nm wavelengths. At 850 nm wavelength, our photon trapping avalanche photodiodes showed 30 times higher gain, an increase from 16% to >60% enhanced absorption efficiency, and a 50% reduction in the full width at half maximum (FWHM) pulse response time close to the breakdown voltage. At 450 nm wavelength, the external quantum efficiency increased from 54% to 82%, while the gain was enhanced more than 20-fold. Therefore, silicon APDs with photon trapping structures exhibited a dramatic increase in absorption compared to control devices. Results suggest very thin devices with fast timing properties and high absorption between the near-ultraviolet and the near infrared region can be manufactured for high-speed applications in biomedical imaging. This study paves the way towards obtaining single photon detectors with photon trapping structures with gains above 106 for the entire visible range.

Concept for using magnetic particle imaging for intraoperative margin analysis in breast-conserving surgery.

Breast-conserving surgery (BCS) is a commonly utilized treatment for early stage breast cancers but has relatively high reexcision rates due to post-surgical identification of positive margins. A fast, specific, sensitive, easy-to-use tool for assessing margins intraoperatively could reduce the need for additional surgeries, and while many techniques have been explored, the clinical need is still unmet. We assess the potential of Magnetic Particle Imaging (MPI) for intraoperative margin assessment in BCS, using a passively or actively tumor-targeted iron oxide agent and two hardware devices: a hand-held Magnetic Particle detector for identifying residual tumor in the breast, and a small-bore MPI scanner for quickly imaging the tumor distribution in the excised specimen. Here, we present both hardware systems and demonstrate proof-of-concept detection and imaging of clinically relevant phantoms.