Efficient Visual Computing With Camera RAW Snapshots.

Conventional cameras capture image irradiance (RAW) on a sensor and convert it to RGB images using an image signal processor (ISP). The images can then be used for photography or visual computing tasks in a variety of applications, such as public safety surveillance and autonomous driving. One can argue that since RAW images contain all the captured information, the conversion of RAW to RGB using an ISP is not necessary for visual computing.

Fast Marching based Tissue Adaptive Delay Estimation for Aberration Corrected Delay and Sum Beamforming in Ultrasound Imaging.

Conventional ultrasound (US) imaging employs the delay and sum (DAS) receive beamforming with dynamic receive focus for image reconstruction due to its simplicity and robustness. However, the DAS beamforming follows a geometrical method of delay estimation with a spatially constant speed-of-sound (SoS) of 1540 m/s throughout the medium irrespective of the tissue in-homogeneity. This approximation leads to errors in delay estimations that accumulate with depth and degrades the resolution, contrast and overall accuracy of the US image.

COVID-19 Vaccination and Its Relation to New-Onset Diabetes: A Narrative Review.

The COVID-19 vaccination has been effective in preventing a lot of complications caused by SARS-CoV-2 and its variants. Meanwhile, diabetes mellitus, one of the root causes of many co-morbidities, exhibited itself during the COVID-19 pandemic and after COVID-19 vaccination. Diabetes mellitus introduced itself in a new perspective, leading to a variety of presentations and causing a significant number of emergency admissions.

Frequency of Gastroparesis Symptoms in Patients With Type-2 Diabetes Mellitus at a Tertiary Care Hospital in Pakistan.

Background Gastroparesis symptoms seem to affect many diabetes mellitus patients. Pakistan has a high prevalence of diabetes, with an estimated 33 million people living with the condition. This study aimed to investigate the frequency of gastroparesis symptoms in patients with type-2 diabetes mellitus (T2DM).

Hybrid Deep Learning and Discrete Wavelet Transform-Based ECG Biometric Recognition for Arrhythmic Patients and Healthy Controls.

The intrinsic and liveness detection behavior of electrocardiogram (ECG) signals has made it an emerging biometric modality for the researcher with several applications including forensic, surveillance and security. The main challenge is the low recognition performance with datasets of large populations, including healthy and heart-disease patients, with a short interval of an ECG signal. This research proposes a novel method with the feature-level fusion of the discrete wavelet transform and a one-dimensional convolutional recurrent neural network (1D-CRNN).

Machine Learning Enhanced Optical Microscopy for the Rapid Morphology Characterization of Silver Nanoparticles.

The rapid characterization of nanoparticles for morphological information such as size and shape is essential for material synthesis as they are the determining factors for the optical, mechanical, and chemical properties and related applications. In this paper, we report a computational imaging platform to characterize nanoparticle size and morphology under conventional optical microscopy. We established a machine learning model based on a series of images acquired by through-focus scanning optical microscopy (TSOM) on a conventional optical microscope.

Spatial and axial resolution limits for mask-based lensless cameras.

One of the open challenges in lensless imaging is understanding how well they resolve scenes in three dimensions. The measurement model underlying prior lensless imagers lacks special structures that facilitate deeper analysis; thus, a theoretical study of the achievable spatio-axial resolution has been lacking. This paper provides such a theoretical framework by analyzing a generalization of a mask-based lensless camera, where the sensor captures z-stacked measurements acquired by moving the sensor relative to an attenuating mask.

Learning to Sense for Coded Diffraction Imaging.

In this paper, we present a framework to learn illumination patterns to improve the quality of signal recovery for coded diffraction imaging. We use an alternating minimization-based phase retrieval method with a fixed number of iterations as the iterative method. We represent the iterative phase retrieval method as an unrolled network with a fixed number of layers where each layer of the network corresponds to a single step of iteration, and we minimize the recovery error by optimizing over the illumination patterns.

Monocular Depth Estimation Using Deep Learning: A Review.

In current decades, significant advancements in robotics engineering and autonomous vehicles have improved the requirement for precise depth measurements. Depth estimation (DE) is a traditional task in computer vision that can be appropriately predicted by applying numerous procedures. This task is vital in disparate applications such as augmented reality and target tracking.

Physics-Guided Neural-Network-Based Inverse Design of a PhotonicPlasmonic Nanodevice for Superfocusing.

Controlling the nanoscale light-matter interaction using superfocusing hybrid photonic-plasmonic devices has attracted significant research interest in tackling existing challenges, including converting efficiencies, working bandwidths, and manufacturing complexities. With the growth in demand for efficient photonic-plasmonic input-output interfaces to improve plasmonic device performances, sophisticated designs with multiple optimization parameters are required, which comes with an unaffordable computation cost. Machine learning methods can significantly reduce the cost of computations compared to numerical simulations, but the input-output dimension mismatch remains a challenging problem.

Oral Mucosal Graft Augmented Anastomotic Urethroplasty for Post Traumatic Urethral Stricture and Distraction Defect: Outcome in 100 Patients.

The surgical procedures of post traumatic posterior urethral stricture and distraction defects range from the extremely simple to the extremely radical. In oral Mucosal Graft Augmented Anastomotic Urethroplasty (OMG AAU) the stricture segment is excised followed by partially re-anastomosis of the dorsal or ventral urethral wall then the reconstruction is completed by placement of oral mucosal graft into the remaining urethral defect. The aim of this study is to determine the impact and assess the effectiveness of this technique, discuss the procedure and outcome and to refine them where found lacking.

SweepCam - Depth-Aware Lensless Imaging Using Programmable Masks.

Lensless cameras, while extremely useful for imaging in constrained scenarios, struggle with resolving scenes with large depth variations. To resolve this, we propose imaging with a set of mask patterns displayed on a programmable mask, and introduce a computational focusing operator that helps to resolve the depth of scene points. As a result, the proposed imager can resolve dense scenes with large depth variations, allowing for more practical applications of lensless cameras.

A Dual Camera System for High Spatiotemporal Resolution Video Acquisition.

This paper presents a dual camera system for high spatiotemporal resolution (HSTR) video acquisition, where one camera shoots a video with high spatial resolution and low frame rate (HSR-LFR) and another one captures a low spatial resolution and high frame rate (LSR-HFR) video. Our main goal is to combine videos from LSR-HFR and HSR-LFR cameras to create an HSTR video. We propose an end-to-end learning framework, AWnet, mainly consisting of a FlowNet and a FusionNet that learn an adaptive weighting function in pixel domain to combine inputs in a frame recurrent fashion.

Motion-adaptive spatio-temporal regularization for accelerated dynamic MRI.

Accelerated magnetic resonance imaging techniques reduce signal acquisition time by undersampling k-space. A fundamental problem in accelerated magnetic resonance imaging is the recovery of quality images from undersampled k-space data. Current state-of-the-art recovery algorithms exploit the spatial and temporal structures in underlying images to improve the reconstruction quality.

Acute life-threatening methaemoglobinaemia following ingestion of chloroquine.

A 25 year old man was rushed to the emergency department when he was found unconscious in his room after taking two chloroquine tablets (600 mg base) for fever prescribed by local practitioner. On examination, the patient was unconscious and deep cyanosis was present on lips, tongue, oral cavity, nail beds and finger tips. Subsequent laboratory investigation revealed methaemoglobin level of 54%.