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Mostrando ítems 61-70 de 174
Xenon: um sistema para gerenciamento de acesso de automóveis por reconhecimento de imagens
(Universidade Tecnológica Federal do ParanáGuarapuavaBrasilTecnologia em Sistemas para InternetUTFPR, 2022-03-28)
The emergence of machine learning algorithms has provided new fields of studies in computing and diverse applicability in the real world. Many of these applications are related to computer vision, which studies image ...
Computed tomographic imaging of the brain of normal neonatal foalsTomografia computarizada del cerebro en potrillos neonatos
(Archivos de Medicina Veterinaria, 2015)
Factors affecting the variability of the Heidelberg Retina Tomograph III measurements in newly diagnosed glaucoma patients
(Conselho Brasileiro de Oftalmologia, 2010-08-01)
PURPOSE: To determine factors associated with the test-retest variability of optic nerve head (ONH) topography measurements with confocal scanning laser ophthalmoscopy (CSLO) in newly diagnosed glaucomatous patients. ...
KoopaML: A Graphical Platform for Building Machine Learning Pipelines Adapted to Health Professionals
Machine Learning (ML) has extended its use in several domains to support complex analyses of data. The medical field, in which significant quantities of data are continuously generated, is one of the domains that can benefit ...
Automatic segmentation of epithelium in cervical whole slide images to assist diagnosis of cervical intraepithelial neoplasia
(Universidad de Chile, 2020)
Cervical Intraepithelial Neoplasia (CIN) is a precancerous state of the cervix, and the correct
diagnosis of its level of severity (CIN grade) allows to determine patient treatment and prevent
invasive carcinoma. It ...
QualIM®: software para treinamento na interpretação de imagens médicas digitais
(Colégio Brasileiro de Radiologia e Diagnóstico por Imagem, 2008-12-01)
OBJECTIVE: A software called QualIM® - Qualificação de Imagens Médicas was developed for training of practitioners in the interpretation of digital mammograms classified according to BI-RADS® categories, utilizing images ...
Improving realism in patient-specific abdominal ultrasound simulation using CycleGANs
(Springer, 2019-08)
Purpose: In this paper, we propose to apply generative adversarial neural networks trained with a cycle consistency loss, or CycleGANs, to improve realism in ultrasound (US) simulation from computed tomography (CT) scans. ...
Auxílio ao diagnóstico automático do esôfago de Barrett utilizando aprendizado de máquina
(Universidade Federal de São CarlosUFSCarPrograma de Pós-Graduação em Ciência da Computação - PPGCCCâmpus São Carlos, 2022-03-28)
Esophageal adenocarcinoma is an illness that is usually hard to detect at the early stages in the presence of Barrett's esohagus. The development of automatic evaluation systems of such illness may be very useful, thus ...
A deep learning model to assess and enhance eye fundus image quality
(Bogotá - Medicina - Maestría en Ingeniería BiomédicaUniversidad Nacional de Colombia - Sede Bogotá, 2020)
Engineering aims to design, build, and implement solutions that will increase and/or improve the life quality of human beings. Likewise, from medicine, solutions are generated for the same purposes, enabling these two ...
Concordancia en la detección de hemorragia subaracnoidea no traumática por medio de tomografías computarizadas de cráneo simple entre clínicos y el reporte radiológico definitivo en un hospital de 4º nivel de atención en Bogotá D.C, Colombia: 2020
Introduction: Subarachnoid hemorrhage (SAH) consists of bleeding in the brain cavity below the arachnoid. Patients who present with SAH are admitted to the various emergency services presenting headaches in up to 25% of ...