Jorge Luis Perez-Gonzalez

• PhD Biomedical Engineering
• Research Associate at National Autonomous University of Mexico

Chagas disease (CD), caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), represents a major public health concern in most of the American continent and causes 12,000 deaths every year. CD clinically manifests in two phases (acute and chronic), and the diagnosis can result in complications due to the difference between phases and the long...

In this work, a novel multimodal learning approach for early prediction of birth weight is presented. Fetal weight is one of the most relevant indicators in the assessment of fetal health status. The aim is to predict early birth weight using multimodal maternal–fetal variables from the first trimester of gestation (Anthropometric data, as well as...

The use of artificial intelligence has shown good performance in the medical imaging area, in particular the deep learning methods based on convolutional neural networks for classification, detection, and/or segmentation tasks. The task addressed in this research work is the segmentation of amastigote nests from histological microphotographs in the...

Las imágenes de ultrasonido médico ofrecen varias ventajas con respecto a otras modalidades como rayos X, tomografía computarizada y resonancia magnética nuclear. Los equipos de ultrasonido son compactos y el tamaño pequeño de la sonda permite al experto tomar imágenes de una amplia variedad de órganos en 2 y 3 dimensiones. Las principales desventa...

This paper aims to introduce an innovative approach to semantic segmentation by leveraging a convolutional neural network (CNN) for predicting the shape and pose parameters of the left ventricle (LV). Our approach involves a modified U-Net architecture with a regression layer as the final stage, as opposed to the traditional classification layer. T...

We propose a methodology to narrow down the selection of design parameters of phantoms for calibrating ultrasound devices. For doing so, we model the phantoms as composite materials. Through a mathematical homogenization technique, the global properties of the phantom are given in terms of the volume fractions of its components, their geometric sha...

Chagas disease (CD) is a neglected parasitic disease caused by the protozoan Trypanosoma cruzi (T. cruzi). The disease has two clinical phases: acute and chronic. In the acute phase, the parasite circulates in the blood. The infection can be asymptomatic or can cause unspecific clinical symptoms. During the chronic phase, the infection can cause el...

In this paper we present a new approach to morphological analysis of magnetic resonance brain images based on graphs. The construction of the graphs is based on the segmentation of brain subregions and measurement of two invariant metrics: discrete compactness and discrete tortuosity. The aim is to construct a graph for a subject at different time...

Selecting the correct material for each application has always been important. Now, with lattice metamaterials engineers can take advantage of the properties of these metamaterials to best suit a specific application. This paper investigates transtibial lower limb socket stress reduction through the implementation of conformal lattice metamaterials...

The global longitudinal strain of the myocardial tissue has been shown to be a better indicator of cardiac pathologies in the subclinical stage than other indices, such as the ejection fraction. This article presents a new deep learning approach for strain estimation in 2D echocardiograms. The proposed method improves the performance of the state o...

In the world, there is a growing need for lower limb prostheses due to a rising number of amputations caused primarily, by diabetic foot. Researchers enable functional and comfortable prostheses through prosthetic design by integrating new technologies applied to the traditional handcrafted method for prosthesis fabrication that is still current. T...

Chagas disease, caused by the Trypanosoma cruzi (T. cruzi) parasite, is the third most common parasitosis worldwide. Most of the infected subjects can remain asymptomatic without an opportune and early detection or an objective diagnostic is not conducted. Frequently, the disease manifests itself after a long time, accompanied by severe heart disea...

Chagas disease is a widely spreaded illness caused by the parasite Trypanosoma cruzi (T. cruzi). Most cases go unnoticed until the accumulated myocardial damage affect the patient. The endomyocardium biopsy is a tool to evaluate sustained myocardial damage, but analyzing histopathological images takes a lot of time and its prone to human error, giv...

During surgical training, it is important for the surgeon develops good motor skills throughout his training. For this reason, various surgical training systems have been developed to enhance these skills. However, one of the great challenges in these training systems is being able to objectively measure the ability and performance of the main surg...

Alzheimer's disease is a multifactorial neurodegenerative disorder preceded by a prodromal stage called mild cognitive impairment (MCI). Early diagnosis of MCI is crucial for delaying the progression and optimizing the treatment. In this study we propose a random forest (RF) classifier to distinguish between MCI and healthy control subjects (HC), i...

El registro rígido es un enfoque que busca alinear dos o más conjuntos de puntos mediante una matriz de transformación. Sus aplicaciones radican en el análisis y reconstrucción de objetos y escenas con propósitos arquitectónicos, industriales o médicos. Uno de los principales problemas es encontrar la matriz de transformación homogénea que efectúe...

Actualmente, existe una creciente necesidad de monitorear fuera de la clínica biomarcadores como la frecuencia cardiaca. Esto ha llevado a desarrollar métodos que aprovechen sensores accesibles a los pacientes, como las cámaras de sus teléfonos. Particularmente, se han establecido métodos de video para extraer el pulso a partir de los movimientos c...

One of the ways to recognize patterns is through the intrinsic information of the object's shape by descriptors that allow us to quantitatively describe the contained shape of the object. In ichthyology, the otolith shape recognition is notable for each fish species, which allows the study of the sagitta otolith in species classification, the compa...

Resumen La Enfermedad de Parkinson es uno de los trastornos neurodegenerativos más impac-tantes en la atención a la salud a nivel mundial. En México, el Instituto Nacional de Neurología y Neurocirugía "Manuel Velasco Suárez" reportó, en el año 2018 una prevalen-cia de 50 casos nuevos por cada 100 mil habitantes al año. Evidencia clínica y hallazgos...

3D ultrasound systems have been widely used for fetal brain structures’ analysis. However, the obtained images present several artifacts such as multiplicative noise and acoustic shadows appearing as a function of acquisition angle. The purpose of this research is to merge several partially occluded ultrasound volumes, acquired by placing the trans...

Quantification of brain growth is crucial for the assessment of fetal well being, for which ultrasound (US) images are the chosen clinical modality. However, they present artefacts, such as acoustic occlusion, especially after the 18th gestational week, when cranial calcification appears. Fetal US volume registration is useful in one or all of the...

The 3D tortuosity determined in several brain areas is proposed as a new morphological biomarker (BM) to be considered in early detection of Alzheimer's disease (AD). It is measured using the sum of angles method and it has proven to be sensitive to anatomical changes that appear in gray and white matter and temporal and parietal lobes during mild...

Birth weight (BW) is an important indicator of neonatal well–being associated with multiple adverse conditions and thus its early estimation may be crucial for timely treatment. In this paper we propose a BW estimation strategy based on Support Vector Regression of a set of multimodal maternal–fetal features obtained in pregnancy’s first trimester....

In this paper, a new method of rigid point cloud registration called Points Registration Learning (PREL) is presented. This algorithm is based on Deep Neural Networks trained by sparse autoencoders and fed with a set of Euclidean and Mahalanobis distance maps. Unlike other reported methods, we do not assume closeness between point clouds or point p...

In this paper, a new scheme of feature extraction based on the registration of two point clouds that model the brain surface area and a cerebral baseline, is presented. The aim is to design an automatic Random Forest classifier based on brain-shape pattern extraction, in order to discriminate among Control subjects, patients with Mild Cognitive Imp...

A new method to address the problem of shadowing in fetal brain ultrasound volumes is presented. The proposed approach is based on the spatial composition of multiple 3-D fetal head projections using the weighted Euclidean norm as an operator. A support vector machine, which is trained with optimal textural features, was used to assign weighting ac...

Ultrasound (US) images of the fetal brain provide the experts with valuable indicators of the fetal development. However as the skull thickens, it obstructs the transmission of the acoustic waves, which in turn occludes the anatomy behind the thickened fetal skull. A viable option to improve the visibility of the fetal brain, before complete calcif...

In this paper we present a fully automatic approach based on texture maps and optimal ellipse detection to segment and obtain measurements of the fetal head. The goals are to segment the fetal head and to measure the biparietal diameter (BPD) and head circumference (HC) using ultrasound images. By incorporating texture maps, morphological operation...

We present a discrete compactness (DC) index, together with a classification scheme, based both on the size and shape features extracted from brain volumes, to determine different aging stages: healthy controls (HC), mild cognitive impairment (MCI), and Alzheimer's disease (AD). A set of 30 brain magnetic resonance imaging (MRI) volumes for each gr...

Reported studies describing normal and abnormal aging based on anatomical MRI analysis do not consider morphological brain changes, but only volumetric measures to distinguish among these processes. This work presents a classification scheme, based both on size and shape features extracted from brain volumes, to determine different aging stages: he...