Leitor óptico de lâminas citológicas com armazenamento em banco de imagens online para agilizar o processo de visualização em laboratório de análises

• Ano de defesa: 2019
• Autor(a) principal: Reis, Leandro Vasconcelos dos
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Curitiba; Brasil; Programa de Pós-Graduação em Engenharia Biomédica; UTFPR
• Palavras-chave em Português: Processamento de imagens - Técnicas digitais; Laboratórios de patologia clínica - Exames; Citodiagnóstico; Engenharia de protótipos; Processamento eletrônico de dados em tempo real; Computação em nuvem; Imagens digitais; Banco de dados em linha; Engenharia biomédica; Image processing - Digital techniquesValidação; Pathological laboratories - Examinations; Cytodiagnosis; Prototypes, Engineering; Real-time data processing; Cloud computing; Digital images; Online databases; Biomedical engineering; CNPQ::ENGENHARIAS::ENGENHARIA BIOMEDICA::ENGENHARIA MEDICA::INSTRUMENTACAO ODONTOLOGICA E MEDICO-HOSPITALAR; Engenharia Biomédica
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/4184

At present the clinical laboratories are offering exams in which they are not able to perform them, due to the lack of equipment or even lack of specialized manpower, with which the exams are collected in a laboratory and sent to a second laboratory which will do the whole analysis. The problem with this practice is that it makes the examination vulnerable to procedural errors and delays in patient response. Based on this understanding, the project aims to build a prototype to collect cytological slides, converting them into digital images and making them available in real time through a cloud platform for analysis laboratories. In this way, the laboratories can eliminate the transport process, reducing the time taken between collection and access of the slides, aiming to improve the time of return of the results of the exams to the patients and to reduce errors in the procedures of the exams. The collector module was developed completely autonomous; Inside there is an embedded computer (Raspberry PI) that works like a normal microcomputer. It has a 5 Megapixel digital camera, especially for the Raspberry PI, which collects the physical slides, transforming them into digital images through a local system. The local image system was developed with Javascript and HTML5, and runs on the local Node.JS server with Firebase CLI in the Raspberry browser. The platform that receives the images and the data of the exams, goes online 24 hours by 7 days of the week. It is hosted on a server in the cloud that maintains access to the service and connects to Google Firebase. This in turn stores and manages all data and system images.