Automated tumor segmentation in thermographic breast images.

Identifying and delineating suspicious regions in thermal breast images poses significant challenges for radiologists during the examination and interpretation of thermogram images. This paper aims to tackle concerns related to enhancing the differentiation between cancerous regions and the background to achieve uniformity in the intensity of breast cancer's (BC) existence. Furthermore, it aims to effectively segment tumors that exhibit limited contrast with the background and extract relevant features that can distinguish tumors from the surrounding tissue.

Distinctions between Choroidal Neovascularization and Age Macular Degeneration in Ocular Disease Predictions via Multi-Size Kernels ξcho-Weighted Median Patterns.

Age-related macular degeneration is a visual disorder caused by abnormalities in a part of the eye's retina and is a leading source of blindness. The correct detection, precise location, classification, and diagnosis of choroidal neovascularization (CNV) may be challenging if the lesion is small or if Optical Coherence Tomography (OCT) images are degraded by projection and motion. This paper aims to develop an automated quantification and classification system for CNV in neovascular age-related macular degeneration using OCT angiography images.

COVID: Automatic COVID-19 CT Image-Based Classification and Visualization Platform Utilizing Virtual and Augmented Reality Technologies.

Recently many studies have shown the effectiveness of using augmented reality (AR) and virtual reality (VR) in biomedical image analysis. However, they are not automating the COVID level classification process. Additionally, even with the high potential of CT scan imagery to contribute to research and clinical use of COVID-19 (including two common tasks in lung image analysis: segmentation and classification of infection regions), publicly available data-sets are still a missing part in the system care for Algerian patients.

Quantifying time-dependent structural and mechanical properties of UV-aged LDPE power cables insulations.

This paper reports effects of ultraviolet (UV) light radiation on the physicochemical, electrical and mechanical properties of low-density polyethylene (LDPE) cable insulating materials. Changes in structural and morphological properties of UV-aged samples were characterized by various analytical methods such as attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM) and atomic force microscopy (AFM). Additionally, elongation at break, tensile strength, dielectric strength, and optical properties were also evaluated.

Virtual Reality visualization for computerized COVID-19 lesion segmentation and interpretation.

Coronavirus disease (COVID-19) is a severe infectious disease that causes respiratory illness and has had devastating medical and economic consequences globally. Therefore, early, and precise diagnosis is critical to control disease progression and management. Compared to the very popular RT-PCR (reverse-transcription polymerase chain reaction) method, chest CT imaging is a more consistent, sensible, and fast approach for identifying and managing infected COVID-19 patients, specifically in the epidemic area.

Automatic COVID-19 lung infected region segmentation and measurement using CT-scans images.

History shows that the infectious disease (COVID-19) can stun the world quickly, causing massive losses to health, resulting in a profound impact on the lives of billions of people, from both a safety and an economic perspective, for controlling the COVID-19 pandemic. The best strategy is to provide early intervention to stop the spread of the disease. In general, Computer Tomography (CT) is used to detect tumors in pneumonia, lungs, tuberculosis, emphysema, or other pleura (the membrane covering the lungs) diseases.

The Base Frame of the Algerian E-Health System: Methodology to Select the IHE Integration Profiles and the Standards to Control Interoperability.

The use of standards and Integrating the Healthcare Enterprise (IHE) is a crucial technique for supporting, monitoring and controlling the integration profiles in healthcare organization systems. The risk of "no-interoperability" increases when several standards are used. Lack of experience in developing countries, particularly in Algeria, increases this risk.

Low-contrast X-ray enhancement using a fuzzy gamma reasoning model.

X-ray images play an important role in providing physicians with satisfactory information correlated to fractures and diseases; unfortunately, most of these images suffer from low contrast and poor quality. Thus, enhancement of the image will increase the accuracy of correct information on pathologies for an autonomous diagnosis system. In this paper, a new approach for low-contrast X-ray image enhancement based on brightness adjustment using a fuzzy gamma reasoning model (FGRM) is proposed.

Electrochemical synthesis of n-type ZnS layers on p-CuO/n-ZnO heterojunctions with different deposition temperatures.

Metal oxide p-n heterojunctions consisting of p-CuO/n-ZnO/n-ZnS nanostructures were deposited on an ITO substrate by three-step electrodeposition. The effect of ZnS layer deposition temperature on the properties of the heterojunction was investigated by different techniques. The Mott-Schottky analysis confirmed the n-type conductivity for ZnO and ZnS and p-type conductivity for the CuO layer, respectively.

Covariance matrix based fall detection from multiple wearable sensors.

Falls are among the critical accidents experienced by elderly people and patients carrying some diseases. Subsequently, the detection and prevention of falls have become a hot research and industrial topic. This is due to the fact that falls are behind numerous irreversible injuries, or even death, and are weighting on the budgets of the health services.

Micro-Hall Sensors Based on Two-Dimensional Molybdenum Diselenide.

Sensors and electronic devices based on semiconductors in their two-dimensional forms have many advantages. In this paper, we studied micro-Hall sensors based on two-dimensional molybdenum diselenide for the first time. The micro-Hall sensor based on a Ti/MoSe₂/Ti structure clearly showed a linear dependence of the Hall voltage as a function of the magnetic field, with a magnetic sensitivity of ∼16 V/AT.

Fuzzy ART-based place recognition for visual loop closure detection.

The automatic place recognition problem is one of the key challenges in SLAM approaches for loop closure detection. Most of the appearance-based solutions to this problem share the idea of image feature extraction, memorization, and matching search. The weakness of these solutions is the storage and computational costs which increase drastically with the environment size.