Bone scan images dataset for study of bone metastases in adult breast cancer patients at IICS-UNA, Paraguay.

This article presents 582 bone scan images from 291 adult patients who attended the Nuclear Medicine Service at the Instituto de Investigaciones en Ciencias de la Salud (IICS) of the Universidad Nacional de Asunción (UNA), Paraguay, between 2020 and 2024. The images were acquired using trimodal SPECT-CT-PET equipment, model AnyScan SCP, and the MEDISO brand. Approximately 20 mCi of technetium-99m methylene diphosphonate (Tc-MDP) was administered to each patient, producing whole-body planar images in anterior and posterior projections of the axial and appendicular skeleton with a resolution of 256 × 1024 pixels.

Thyroid scan image dataset for the study of thyroid pathologies in adult patients.

This article presents a dataset containing 641 images of Thyroid Gammagraphies studies corresponding to 235 patients over 18 years of age that were acquired in the period from 2016 to 2024 at the Nuclear Medicine Service of the of the (IICS - UNA), Paraguay. First, the Thyroid Gammagraphies images were acquired according to the acquisition protocol described in this article. The thyroid scintigraphies images were acquired using trimodal SPECT-CT-PET equipment, model AnyScan SCP, MEDISO brand.

Dataset of fundus images for the diagnosis of ocular toxoplasmosis.

Toxoplasmosis chorioretinitis is commonly diagnosed by an ophthalmologist through the evaluation of the fundus images of a patient. Early detection of these lesions may help to prevent blindness. In this article we present a data set of fundus images labeled into three categories: healthy eye, inactive and active chorioretinitis.

Automatic Diagnosis of Diabetic Retinopathy from Fundus Images Using Neuro-Evolutionary Algorithms.

Due to the presence of high glucose levels, diabetes mellitus (DM) is a widespread disease that can damage blood vessels in the retina and lead to loss of the visual system. To combat this disease, called Diabetic Retinopathy (DR), retinography, using images of the fundus of the retina, is the most used method for the diagnosis of Diabetic Retinopathy. The Deep Learning (DL) area achieved high performance for the classification of retinal images and even achieved almost the same human performance in diagnostic tasks.

Correlation Between Quality Evaluation Metrics and Teeth Detection Results in Panoramic X-Rays Using Deep Learning.

Panoramic images are one of the most requested exams by dentists for allowing the visualization of the entire mouth. Interpreting X-ray images is a time-consuming task in which misdiagnoses can occur due to the inexperience or fatigue of professionals. In this work, we applied different image enhancement techniques as a pre-processing step to determine which image features correlate with improvements in teeth detection in panoramic images using deep learning architectures.

Distribution level electric current consumption and meteorological data set of the east region of Paraguay.

This paper presents a data set with information on meteorological data and electricity consumption in the department of Alto Paraná, Paraguay. The meteorological data were registered every three hours at the Aeropuerto Guarani, Department of Alto Paraná, which belongs to the Dirección Nacional de Aeronáutica Civil of Paraguay. The final data consists of a total of 22.

A Trust-Based Methodology to Evaluate Deep Learning Models for Automatic Diagnosis of Ocular Toxoplasmosis from Fundus Images.

In the automatic diagnosis of ocular toxoplasmosis (OT), Deep Learning (DL) has arisen as a powerful and promising approach for diagnosis. However, despite the good performance of the models, decision rules should be interpretable to elicit trust from the medical community. Therefore, the development of an evaluation methodology to assess DL models based on interpretability methods is a challenging task that is necessary to extend the use of AI among clinicians.

Dataset from fundus images for the study of diabetic retinopathy.

This article presents a database containing 757 color fundus images acquired at the Department of Ophthalmology of the Hospital de Clínicas, Facultad de Ciencias Médicas (FCM), Universidad Nacional de Asunción (UNA), Paraguay. Firstly, the retinal images were acquired with a clinical procedure presented in this paper. The acquisition of the retinographies was made through the Visucam 500 camera of the Zeiss brand.

Automatic Diagnosis of Ocular Toxoplasmosis from Fundus Images with Residual Neural Networks.

Ocular toxoplasmosis (OT) is commonly diagnosed through the analysis of fundus images of the eye by a specialist. Despite Deep Learning being widely used to process and recognize pathologies in medical images, the diagnosis of ocular toxoplasmosis(OT) has not yet received much attention. A predictive computational model is a valuable time-saving option if used as a support tool for the diagnosis of OT.

Panoramic Dental Radiography Image Enhancement Using Multiscale Mathematical Morphology.

Panoramic dental radiography is one of the most used images of the different dental specialties. This radiography provides information about the anatomical structures of the teeth. The correct evaluation of these radiographs is associated with a good quality of the image obtained.

A multi-objective approach for designing optimized operation sequence on binary image processing.

In binary image segmentation, the choice of the order of the operation sequence may yield to suboptimal results. In this work, we propose to tackle the associated optimization problem via multi-objective approach. Given the original image, in combination with a list of morphological, logical and stacking operations, the goal is to obtain the ideal output at the lowest computational cost.

Computational Inference of Gene Co-Expression Networks for the identification of Lung Carcinoma Biomarkers: An Ensemble Approach.

Gene Networks (GN), have emerged as an useful tool in recent years for the analysis of different diseases in the field of biomedicine. In particular, GNs have been widely applied for the study and analysis of different types of cancer. In this context, Lung carcinoma is among the most common cancer types and its short life expectancy is partly due to late diagnosis.

Entropy and Contrast Enhancement of Infrared Thermal Images Using the Multiscale Top-Hat Transform.

Discrete entropy is used to measure the content of an image, where a higher value indicates an image with richer details. Infrared images are capable of revealing important hidden targets. The disadvantage of this type of image is that their low contrast and level of detail are not consistent with human visual perception.

Structure Optimization for Large Gene Networks Based on Greedy Strategy.

In the last few years, gene networks have become one of most important tools to model biological processes. Among other utilities, these networks visually show biological relationships between genes. However, due to the large amount of the currently generated genetic data, their size has grown to the point of being unmanageable.