Skin Type Diversity in Skin Lesion Datasets: A Review.

Purpose Of Review: Skin type diversity in image datasets refers to the representation of various skin types. This diversity allows for the verification of comparable performance of a trained model across different skin types. A widespread problem in datasets involving human skin is the lack of verifiable diversity in skin types, making it difficult to evaluate whether the performance of the trained models generalizes across different skin types.

LightNet: A Novel Lightweight Convolutional Network for Brain Tumor Segmentation in Healthcare.

Diagnosis, treatment planning, surveillance, and the monitoring of clinical trials for brain diseases all benefit greatly from neuroimaging-based tumor segmentation. Recently, Convolutional Neural Networks (CNNs) have demonstrated promising results in enhancing the efficiency of image-based brain tumor segmentation. Most current work on CNNs, however, is devoted to creating increasingly complicated convolution modules to improve performance, which in turn raises the computing cost of the model.

SEDIQA: Sound Emitting Document Image Quality Assessment in a Reading Aid for the Visually Impaired.

For visually impaired people (VIPs), the ability to convert text to sound can mean a new level of independence or the simple joy of a good book. With significant advances in optical character recognition (OCR) in recent years, a number of reading aids are appearing on the market. These reading aids convert images captured by a camera to text which can then be read aloud.

CleanPage: Fast and Clean Document and Whiteboard Capture.

The move from paper to online is not only necessary for remote working, it is also significantly more sustainable. This trend has seen a rising need for the high-quality digitization of content from pages and whiteboards to sharable online material. However, capturing this information is not always easy nor are the results always satisfactory.

A Systematic Review of Urban Navigation Systems for Visually Impaired People.

Blind and Visually impaired people (BVIP) face a range of practical difficulties when undertaking outdoor journeys as pedestrians. Over the past decade, a variety of assistive devices have been researched and developed to help BVIP navigate more safely and independently. In addition, research in overlapping domains are addressing the problem of automatic environment interpretation using computer vision and machine learning, particularly deep learning, approaches.

MATtrack: A MATLAB-Based Quantitative Image Analysis Platform for Investigating Real-Time Photo-Converted Fluorescent Signals in Live Cells.

We introduce here MATtrack, an open source MATLAB-based computational platform developed to process multi-Tiff files produced by a photo-conversion time lapse protocol for live cell fluorescent microscopy. MATtrack automatically performs a series of steps required for image processing, including extraction and import of numerical values from Multi-Tiff files, red/green image classification using gating parameters, noise filtering, background extraction, contrast stretching and temporal smoothing. MATtrack also integrates a series of algorithms for quantitative image analysis enabling the construction of mean and standard deviation images, clustering and classification of subcellular regions and injection point approximation.

Tracking protein dynamics with photoconvertible Dendra2 on spinning disk confocal systems.

Understanding the dynamic properties of cellular proteins in live cells and in real time is essential to delineate their function. In this context, we introduce the Fluorescence Recovery After Photobleaching-Photoactivation unit (Andor) combined with the Nikon Eclipse Ti E Spinning Disk (Andor) confocal microscope as an advantageous and robust platform to exploit the properties of the Dendra2 photoconvertible fluorescent protein (Evrogen) and analyse protein subcellular trafficking in living cells. A major advantage of the spinning disk confocal is the rapid acquisition speed, enabling high temporal resolution of cellular processes.

A monocular marker-free gait measurement system.

This paper presents a new, user-friendly, portable motion capture and gait analysis system for capturing and analyzing human gait, designed as a telemedicine tool to monitor remotely the progress of patients through treatment. The system requires minimal user input and simple single-camera filming (which can be acquired from a basic webcam) making it very accessible to nontechnical, nonclinical personnel. This system can allow gait studies to acquire a much larger data set and allow trained gait analysts to focus their skills on the interpretation phase of gait analysis.