Olmo Zavala-Romero

Florida State University | FSU

This study utilizes Deep Neural Networks (DNN) to improve the K‐Profile Parameterization (KPP) for the vertical mixing effects in the ocean's surface boundary layer turbulence. The deep neural networks were trained using 11‐year turbulence‐resolving solutions, obtained by running a large eddy simulation model for Ocean Station Papa, to predict the...

During the period of 2018–2022, there were six named Loop Current Eddy (LCE) shedding events in the central Gulf of Mexico (GoM). LCEs form when a large anticyclonic eddy (AE) separates from the main Loop Current (LC) and propagates westward. In doing so, each LCE traps and advects warmer, saltier waters with lower Chlorophyll-a (Chl-a) concentrati...

This study utilizes Deep Neural Networks (DNN) to improve the K-Profile Parameterization (KPP) for the vertical mixing effects in the ocean’s surface boundary layer turbulence. The DNNs were trained using 11-year turbulence-resolving solutions, obtained by running a large eddy simulation model for Ocean Station Papa, to predict the turbulence veloc...

Deep learning models have demonstrated remarkable success in fields such as language processing and computer vision, routinely employed for tasks like language translation, image classification, and anomaly detection. Recent advancements in ocean sciences, particularly in data assimilation (DA), suggest that machine learning can emulate dynamical m...

Uterine muscle contractility is essential for reproductive processes including sperm and embryo transport, and during the uterine cycle to remove menstrual effluent. Even still, uterine contractions have primarily been studied in the context of preterm labor. This is partly due to a lack of methods for studying the uterine muscle contractility in t...

The persistent increase in marine plastic litter has become a major global concern, with one of the highest plastic concentrations in the world’s oceans found in the Wider Caribbean Region (WCR). In this study, we use marine plastic litter tracking simulations to investigate where marine plastic accumulates, i.e., hotspots, in the WCR and how the a...

Simple Summary In this study, we built clinical- and radiomics-based models to predict lesions/patients at low risk based on a combined clinical-genomic classification system. Eighty-three multi-parametric MRI exams from 78 men were analyzed. Several models for lesion classification were built using a minimal clinical variables subset and radiomic...

Background/Hypothesis MRI-guided online adaptive radiotherapy (MRI-g-OART) improves target coverage and organs-at-risk (OARs) sparing in radiation therapy (RT). For patients with locally advanced cervical cancer (LACC) undergoing RT, changes in bladder and rectal filling contribute to large inter-fraction target volume motion. We hypothesized that...

Purpose/Objective(s) Recently identified changes in brain during daily MRI-guided radiation therapy (MRgRT) of patients with glioblastoma (GBM) can permit adaptive radiotherapy. However, daily changes can be subtle to detect and difficult to evaluate volumetrically without significant manual effort. The aim of this study is to develop a deep learni...

Plastic is the most abundant type of marine litter and it is found in all of the world’s oceans and seas, even in remote areas far from human activities. It is a major concern because plastics remain in the oceans for a long time. To address questions that are of great interest to the international community as it seeks to attend to the major sourc...

PurposeDevelop a deep-learning-based segmentation algorithm for prostate and its peripheral zone (PZ) that is reliable across multiple MRI vendors.Methods This is a retrospective study. The dataset consisted of 550 MRIs (Siemens-330, General Electric[GE]-220). A multistream 3D convolutional neural network is used for automatic segmentation of the p...

Computer-aided detection and diagnosis (CAD) systems have the potential to improve robustness and efficiency compared to traditional radiological reading of magnetic resonance imaging (MRI). Fully automated segmentation of the prostate is a crucial step of CAD for prostate cancer, but visual inspection is still required to detect poorly segmented c...

An oil spill particle dispersion model implemented in Julia, a high-performance programming language, and Matlab is described. The model is based on a Lagrangian particle tracking algorithm with a second-order Runge-Kutta scheme. It uses ocean currents from the Hybrid Coordinate Ocean Model (HYCOM) and winds from the Weather Research and Forecastin...

We present a radiomics-based approach developed for the SPIE-AAPM-NCI PROSTATEx challenge. The task was to classify clinically significant prostate cancer in multiparametric (mp) MRI. Data consisted of a "training dataset" (330 suspected lesions from 204 patients) and a "test dataset" (208 lesions/140 patients). All studies included T2-weighted (T2...

Brain imaging studies identified brain networks that play a key role in nicotine dependence-related behavior. Functional connectivity of the brain is dynamic; it changes over time due to different causes such as learning, or quitting a habit. Functional connectivity analysis is useful in discovering and comparing patterns between functional magneti...

This work describes OWGIS, an open source Java web application that creates Web GIS sites by automatically writing HTML and JavaScript code. OWGIS is configured by XML files that define which layers (geographic datasets) will be displayed on the websites. This project uses several Open Geospatial Consortium standards to request data from typical ma...

OWGIS version 2.0 is an open source Java and JavaScript application that builds easily configurable Web GIS sites for desktop and mobile devices. This version of OWGIS generates mobile interfaces based on HTML5 technology and can be used to create mobile applications. The style of the generated websites is modified using COMPASS, a well known CSS A...

Analyzing soft-tissue structures is particularly challenging due to the lack of homologous landmarks that can be reliably identified across time and specimens. This is particularly true when data are to be collected under field conditions. Here, we present a method that combines photogrammetric techniques and geometric morphometrics methods (GMM) t...

Small and non-mass-enhancing lesions are diagnostically challenging and easily missed in a routine clinical diagnosis. Compared to mass-enhancing lesions, they show fundamentally di®erent morphologies and kinetic characteristics. To overcome these limitations an automated analysis of such tumors is proposed to determine adequate shape and dynamica...

An OpenCL implementation of the Active Contours Without Edges algorithm is presented. The proposed algorithm uses the General Purpose Computing on Graphics Processing Units (GPGPU) to accelerate the original model by parallelizing the two main steps of the segmentation process, the computation of the Signed Distance Function (SDF) and the evolution...

Spatio-temporal feature extraction represents a challenge however critical step for the differential diagnosis of non-mass-enhancing lesions. The atypical dynamical behavior of these lesions paired with non well-defined tumor borders requires novel approaches to obtain representative features for a subsequent automated diagnosis. We evaluate the pe...

A new approach to optimize the parameters of a gradient-based optical flow model using a parallel genetic algorithm (GA) is proposed. The main characteristics of the optical flow algorithm are its bio-inspiration and robustness against contrast, static patterns and noise, besides working consistently with several optical illusions where other algor...

Modern geomatic technologies—and particularly geoscientific, digital, and online multimedia cartography—represent one response to the growing demand for climatic information by the scientific community and general users. The Digital Climatic Atlas of Mexico (DCAM) fills the need to have readily accessible climate information about Mexico, Central A...