Medical imaging compression for high-performance storage systems

Detalhes bibliográficos
Autor(a) principal: Almeida, André Ribeiro
Data de Publicação: 2022
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10773/36680
Resumo: Information systems and the medical subject are two widespread topics that have interwoven so that medical help could become more efficient. This relation has bred the PACS and the international standard DICOM directed to the organization of digital medical information. The concept of image compression is applied to most images throughout the web. The compression formats used for medical imaging have become outdated. The new formats that have been developed in the past few years are candidates for replacing the old ones in such contexts, possibly enhancing the process. Before they are adopted, an evaluation should be carried out that validates their admissibility. This dissertation reviews the state of the art of medical imaging information systems, namely PACS systems and the DICOM standard. Furthermore, some topics of image compression are covered, such as the metrics for evaluating the algorithms’ performance, finalizing with a survey of four modern formats: JPEG XL, AVIF, and WebP. Two software projects were developed, where the first one carries out an analysis of the formats based on the metrics, using DICOM datasets and producing results that can be used for creating recommendations on the format’s use. The second consists of an application that encodes and decodes medical images with the formats covered in this dissertation. This proof-of-concept works as a medical imaging archive for the storage, distribution, and visualization of compressed data.
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spelling Medical imaging compression for high-performance storage systemsDigital imagingMedical imagingImage compressionImage file formatMetricsDICOMPACSJPEG XLAVIFWebPImage qualityInformation systems and the medical subject are two widespread topics that have interwoven so that medical help could become more efficient. This relation has bred the PACS and the international standard DICOM directed to the organization of digital medical information. The concept of image compression is applied to most images throughout the web. The compression formats used for medical imaging have become outdated. The new formats that have been developed in the past few years are candidates for replacing the old ones in such contexts, possibly enhancing the process. Before they are adopted, an evaluation should be carried out that validates their admissibility. This dissertation reviews the state of the art of medical imaging information systems, namely PACS systems and the DICOM standard. Furthermore, some topics of image compression are covered, such as the metrics for evaluating the algorithms’ performance, finalizing with a survey of four modern formats: JPEG XL, AVIF, and WebP. Two software projects were developed, where the first one carries out an analysis of the formats based on the metrics, using DICOM datasets and producing results that can be used for creating recommendations on the format’s use. The second consists of an application that encodes and decodes medical images with the formats covered in this dissertation. This proof-of-concept works as a medical imaging archive for the storage, distribution, and visualization of compressed data.Os sistemas de informação e o assunto médico são dois temas difundidos que se entrelaçam para que a ajuda médica se torne mais eficiente. Essa relação deu origem ao PACS e ao padrão internacional DICOM direcionado à organização da informação médica digital. O conceito de compressão de imagem é aplicado à maioria das imagens em toda a web. Os formatos de compressão usados para imagens médicas tornaram-se desatualizados. Os novos formatos desenvolvidos nos últimos anos são candidatos a substituir os antigos nesses contextos, possivelmente potencializando o processo. Antes de serem adotados, deve ser realizada uma avaliação que valide sua admissibilidade. Esta dissertação revisa o estado da arte dos sistemas de informação de imagens médicas, nomeadamente os sistemas PACS e a norma DICOM. Além disso, são abordados alguns tópicos de compressão de imagens, como as métricas para avaliação do desempenho dos algoritmos, finalizando com um levantamento de três formatos modernos: JPEG XL, AVIF e WebP. Foram desenvolvidos dois projetos de software, onde o primeiro realiza uma análise dos formatos com base nas métricas, utilizando conjuntos de dados DICOM e produzindo resultados que podem ser utilizados para a criação de recomendações sobre o uso do formato. A segunda consiste numa aplicação capaz de codificar e descodificar imagens médicas com os formatos abordados nesta dissertação. Essa prova de conceito funciona como um arquivo de imagens médicas para armazenamento, distribuição e visualização de dados compactados.2023-03-28T11:01:20Z2022-12-15T00:00:00Z2022-12-15info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10773/36680engAlmeida, André Ribeiroinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T12:10:39Zoai:ria.ua.pt:10773/36680Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:07:22.805898Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Medical imaging compression for high-performance storage systems
title Medical imaging compression for high-performance storage systems
spellingShingle Medical imaging compression for high-performance storage systems
Almeida, André Ribeiro
Digital imaging
Medical imaging
Image compression
Image file format
Metrics
DICOM
PACS
JPEG XL
AVIF
WebP
Image quality
title_short Medical imaging compression for high-performance storage systems
title_full Medical imaging compression for high-performance storage systems
title_fullStr Medical imaging compression for high-performance storage systems
title_full_unstemmed Medical imaging compression for high-performance storage systems
title_sort Medical imaging compression for high-performance storage systems
author Almeida, André Ribeiro
author_facet Almeida, André Ribeiro
author_role author
dc.contributor.author.fl_str_mv Almeida, André Ribeiro
dc.subject.por.fl_str_mv Digital imaging
Medical imaging
Image compression
Image file format
Metrics
DICOM
PACS
JPEG XL
AVIF
WebP
Image quality
topic Digital imaging
Medical imaging
Image compression
Image file format
Metrics
DICOM
PACS
JPEG XL
AVIF
WebP
Image quality
description Information systems and the medical subject are two widespread topics that have interwoven so that medical help could become more efficient. This relation has bred the PACS and the international standard DICOM directed to the organization of digital medical information. The concept of image compression is applied to most images throughout the web. The compression formats used for medical imaging have become outdated. The new formats that have been developed in the past few years are candidates for replacing the old ones in such contexts, possibly enhancing the process. Before they are adopted, an evaluation should be carried out that validates their admissibility. This dissertation reviews the state of the art of medical imaging information systems, namely PACS systems and the DICOM standard. Furthermore, some topics of image compression are covered, such as the metrics for evaluating the algorithms’ performance, finalizing with a survey of four modern formats: JPEG XL, AVIF, and WebP. Two software projects were developed, where the first one carries out an analysis of the formats based on the metrics, using DICOM datasets and producing results that can be used for creating recommendations on the format’s use. The second consists of an application that encodes and decodes medical images with the formats covered in this dissertation. This proof-of-concept works as a medical imaging archive for the storage, distribution, and visualization of compressed data.
publishDate 2022
dc.date.none.fl_str_mv 2022-12-15T00:00:00Z
2022-12-15
2023-03-28T11:01:20Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10773/36680
url http://hdl.handle.net/10773/36680
dc.language.iso.fl_str_mv eng
language eng
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instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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