A Short Breast Imaging Reporting and Data System-Based Description for Classification of Breast Mass Grade.

Identifying breast masses is relevant in early cancer detection. Automatic identification using computational methods helps assist medical experts with this task. Although high values have been reported in breast mass classification from digital mammograms, most results have focused on a general benign/malignant classification.

Lure Monitoring for Mediterranean Fruit Fly Traps Using Air Quality Sensors.

Effective pest population monitoring is crucial in precision agriculture, which integrates various technologies and data analysis techniques for enhanced decision-making. This study introduces a novel approach for monitoring lures in traps targeting the Mediterranean fruit fly, utilizing air quality sensors to detect total volatile organic compounds (TVOC) and equivalent carbon dioxide (eCO). Our results indicate that air quality sensors, specifically the SGP30 and ENS160 models, can reliably detect the presence of lures, reducing the need for frequent physical trap inspections and associated maintenance costs.

Shadow Effect for Small Insect Detection by W-Band Pulsed Radar.

In radar entomology, one primary challenge is detecting small species (smaller than 5 cm) since these tiny insects reflect radiation that can be poorly observable and, therefore, difficult to interpret. After a literature search on radar entomology, this research found few works where it has been possible to sense insects with dimensions smaller than 5 cm using radars. This paper describes different methodologies to detect Mediterranean fruit flies with 5-6 mm sizes using a pulsed W-band radar and presents the experimental results that validate the procedures.

Adaptive Feature Extraction for Blood Vessel Segmentation and Contrast Recalculation in Laser Speckle Contrast Imaging.

Microvasculature analysis in biomedical images is essential in the medical area to evaluate diseases by extracting properties of blood vessels, such as relative blood flow or morphological measurements such as diameter. Given the advantages of Laser Speckle Contrast Imaging (LSCI), several studies have aimed to reduce inherent noise to distinguish between tissue and blood vessels at higher depths. These studies have shown that computing Contrast Images (CIs) with Analysis Windows (AWs) larger than standard sizes obtains better statistical estimators.

Characterization of Nuclear Pleomorphism and Tubules in Histopathological Images of Breast Cancer.

Breast cancer (BC) diagnosis is made by a pathologist who analyzes a portion of the breast tissue under the microscope and performs a histological evaluation. This evaluation aims to determine the grade of cellular differentiation and the aggressiveness of the tumor by the Nottingham Grade Classification System (NGS). Nowadays, digital pathology is an innovative tool for pathologists in diagnosis and acquiring new learning.

ECG-Based Identification of Sudden Cardiac Death through Sparse Representations.

Sudden Cardiac Death (SCD) is an unexpected sudden death due to a loss of heart function and represents more than 50% of the deaths from cardiovascular diseases. Since cardiovascular problems change the features in the electrical signal of the heart, if significant changes are found with respect to a reference signal (healthy), then it is possible to indicate in advance a possible SCD occurrence. This work proposes SCD identification using Electrocardiogram (ECG) signals and a sparse representation technique.

Visible-NIR Image Fusion Based on Top-Hat Transform.

The near-infrared band of the electromagnetic spectrum has become an important tool for enhancing image quality. Commonly, outdoor color images are degraded by bad weather conditions that lead to a loss of contrast and fine details in color images since light scattering produces attenuation and smoothing effects. Despite the fact that current Visible-NIR fusion methods achieve image enhancement features, some issues like edge preservation and color oversaturation still need to be addressed.

Deep Learning Classification for Diabetic Foot Thermograms.

According to the World Health Organization (WHO), Diabetes Mellitus (DM) is one of the most prevalent diseases in the world. It is also associated with a high mortality index. Diabetic foot is one of its main complications, and it comprises the development of plantar ulcers that could result in an amputation.

Space-directional approach to improve blood vessel visualization and temporal resolution in laser speckle contrast imaging.

Blood flow is a parameter used to diagnose vascular diseases based on flow speed, blood pressure, and vessel size. Different techniques have been developed to estimate the relative blood flow speed and to improve the visualization of deep blood vessels; one such technique is laser speckle contrast imaging (LSCI). LSCI images contain a high level of noise mainly when deep blood vessels are imaged.

On the use of Action Units and fuzzy explanatory models for facial expression recognition.

Facial expression recognition is related to the automatic identification of affective states of a subject by computational means. Facial expression recognition is used for many applications, such as security, human-computer interaction, driver safety, and health care. Although many works aim to tackle the problem of facial expression recognition, and the discriminative power may be acceptable, current solutions have limited explicative power, which is insufficient for certain applications, such as facial rehabilitation.

Visualization of deep blood vessels using principal component analysis based laser speckle imaging.

Visualization of blood vessels is a fundamental task in the evaluation of the health and biological integrity of tissue. Laser speckle contrast imaging (LSCI) is a non-invasive technique to determine the blood flow in superficial or exposed vasculature. However, the high scattering of biological tissue hinders the visualization of those structures.

Use of kurtosis for locating deep blood vessels in raw speckle imaging using a homogeneity representation.

Visualization of deep blood vessels in speckle images is an important task as it is used to analyze the dynamics of the blood flow and the health status of biological tissue. Laser speckle imaging is a wide-field optical technique to measure relative blood flow speed based on the local speckle contrast analysis. However, it has been reported that this technique is limited to certain deep blood vessels (about ? = 300 ?? ? m ) because of the high scattering of the sample; beyond this depth, the quality of the vessel’s image decreases.

Detection and measurement of the intracellular calcium variation in follicular cells.

This work presents a new method for measuring the variation of intracellular calcium in follicular cells. The proposal consists in two stages: (i) the detection of the cell's nuclei and (ii) the analysis of the fluorescence variations. The first stage is performed via watershed modified transformation, where the process of labeling is controlled.

Morphological rational operator for contrast enhancement.

Contrast enhancement is an important task in image processing that is commonly used as a preprocessing step to improve the images for other tasks such as segmentation. However, some methods for contrast improvement that work well in low-contrast regions affect good contrast regions as well. This occurs due to the fact that some elements may vanish.