PurposeAutomated diagnosis of urogenital schistosomiasis using digital microscopy images of urine slides is an essential step toward the elimination of schistosomiasis as a disease of public health concern in Sub-Saharan African countries. We create a robust image dataset of urine samples obtained from field settings and develop a two-stage diagnosis framework for urogenital schistosomiasis.ApproachUrine samples obtained from field settings were captured using the Schistoscope device, and S. haematobium eggs present in the images were manually annotated by experts to create the SH dataset. Next, we develop a two-stage diagnosis framework, which consists of semantic segmentation of S. haematobium eggs using the DeepLabv3-MobileNetV3 deep convolutional neural network and a refined segmentation step using ellipse fitting approach to approximate the eggs with an automatically determined number of ellipses. We defined two linear inequality constraints as a function of the overlap coefficient and area of a fitted ellipses. False positive diagnosis resulting from over-segmentation was further minimized using these constraints. We evaluated the performance of our framework on 7605 images from 65 independent urine samples collected from field settings in Nigeria, by deploying our algorithm on an Edge AI system consisting of Raspberry Pi + Coral USB accelerator.ResultThe SH dataset contains 12,051 images from 103 independent urine samples and the developed urogenital schistosomiasis diagnosis framework achieved clinical sensitivity, specificity, and precision of 93.8%, 93.9%, and 93.8%, respectively, using results from an experienced microscopist as reference.ConclusionOur detection framework is a promising tool for the diagnosis of urogenital schistosomiasis as our results meet the World Health Organization target product profile requirements for monitoring and evaluation of schistosomiasis control programs.
Significance: Particle field holography is a versatile technique to determine the size and distribution of moving or stationary particles in air or in a liquid without significant disturbance of the sample volume. Although this technique is applied in biological sample analysis, it is limited to small sample volumes, thus increasing the number of measurements per sample. In this work, we characterize the maximum achievable volume limit based on the specification of a given sensor to realize the development of a potentially low-cost, single-shot, large-volume holographic microscope.
Aim: We present mathematical formulas that will aid in the design and development and improve the focusing speed for the numerical reconstruction of registered holograms in particle field holographic microscopes. Our proposed methodology has potential application in the detection of Schistosoma haematobium eggs in human urine samples.
Approach: Using the Fraunhofer holography theory for opaque objects, we derived an exact formula for the maximum diffraction-limited volume for an in-line holographic setup. The proof-of-concept device built based on the derived formulas was experimentally validated with urine spiked with cultured Schistosoma haematobium eggs.
Results: Results obtained show that for urine spiked with Schistosoma haematobium eggs, the volume thickness is limited to several millimeters due to scattering properties of the sample. The distances of the target particles could be estimated directly from the hologram fringes.
Conclusion: The methodology proposed will aid in the development of large-volume holographic microscopes.
Fourier Ptychography is a computational imaging technique able to decouple high resolution from wide field of view, bypassing the diffraction limit of the microscope. Since it does not rely on high precision mechanics or fluorescent imaging, it is of practical interest for implementation in low scale devices. Despite its gains, realizing a functional low-cost setup working at the theoretical limits is challenging due to many factors causing discrepancies between theory and practice. Misalignment of the light emitting diode array (LED-array), optical system aberrations and use of partial coherent sources are common issues which have been addressed with calibration algorithms. However, physical interpretation of how these factors influence the algorithm and cause mismatches between theory and practice has had little attention so far. This work provides a discussion based on simulation results on the effect of the partial coherence of the source. From obtained results, an optimal set of LEDs for data acquisition is described which avoids degeneracy caused by partial coherence and is based on the numerical aperture (NA) of the objective and source parameters such as bandwidth and size.
We present a simple method for the diagnosis of urinary schistosomiasis using an in-line lensless holographic microscope combined with flow cytometry technique. Using simple image processing algorithms and binary image classifier, our system provides automated detection of Schistosoma haematobium eggs in infected urine samples. Registered hologram is reconstructed by applying backpropagation from sensor to sample plane and reconstructed image is automatically analysed for the presence of S. haematobium eggs. Designed for use in a resource-poor laboratory setting, our proposed method has been implemented using a Raspberry Pi computer. From pre-clinical test performed with human urine samples spiked with S. haematobium eggs (approximately 200 eggs per 12 ml of urine), we achieved a sensitivity and specificity of 50.6% and 98.6% respectively. Our proposed method requires no complex sample preparation methods making the system simple to operate and useable in point-of-care diagnosis of urinary schistosomiasis.This method can be optimized to complement existing diagnostic procedures for the detection of S. haematobium eggs and can be deployed to inaccessible remote areas.
We present an integrated optical wavelength meter based on a Si3N4/SiO2 micro ring resonator (operating over a free spectral range of ≈ 2.6 nm) whose output response is immune to temperature changes. The wavelength meter readout is performed by a neural network and a non-linear optimization algorithm. This novel approach ensures a high wavelength estimation precision (≈ 50 pm). We observe a long-term reproducibility of the wavelength meter response over a time interval of one week. We investigate the influence of the ambient temperature on the estimated wavelength. We observe an immunity of the displayed output wavelength to temperature changes of up to several degrees. The temperature-drift immunity appears to be caused by deviations from the theoretically expected (perfect) transmission function of a ring resonator, i.e., caused by deviations that are usually undesired in spectroscopic devices.
This paper presents experimental results of a static aberration control algorithm based on the linear relation be- tween mean square of the aberration gradient and the second moment of point spread function for the generation of control signal input for a deformable mirror (DM). Results presented in the work of Yang et al.1 suggested a good feasibility of the method for correction of static aberration for point and extended sources. However, a practical realisation of the algorithm has not been demonstrated. The goal of this article is to check the method experimentally in the real conditions of the present noise, finite dynamic range of the imaging camera, and system misalignments. The experiments have shown strong dependence of the linearity of the relationship on image noise and overall image intensity, which depends on the aberration level. Also, the restoration capability and the rate of convergence of the AO system for aberrations generated by the deformable mirror are experi- mentally investigated. The presented approach as well as the experimental results finds practical application in compensation of static aberration in adaptive microscopic imaging system.
We have implemented an extended depth of field optical system by wavefront coding with a micromachined membrane deformable mirror. This approach provides a versatile extension to standard wavefront coding based on fixed phase mask. First experimental results validate the feasibility of the use of adaptive optics for variable depth wavefront coding in imaging optical systems.
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