13 research outputs found
Serviços de imagem médica suportados na cloud
Mestrado em Engenharia de Computadores e TelemáticaHoje em dia, as instituições de cuidados de saúde, utilizam a telemedicina para
suportar ambientes colaborativos. Na área da imagem médica digital, a
quantidade de dados tem crescido substancialmente nos últimos anos,
requerendo mais infraestruturas para fornecer um serviço com a qualidade
desejada. Os computadores e dispositivos com acesso à Internet estão
acessíveis em qualquer altura e em qualquer lugar, criando oportunidades para
partilhar e utilizar recursos online. Uma enorme quantidade de processamento
computacional e armazenamento são utilizados como uma comodidade no
quotidiano. Esta dissertação apresenta uma plataforma para suportar serviços
de telemedicina sobre a cloud, permitindo que aplicações armazenem e
comuniquem facilmente, utilizando qualquer fornecedor de cloud. Deste modo,
os programadores não necessitam de se preocupar onde os recursos vão ser
instalados a as suas aplicações não ficam limitadas a um único fornecedor.
Foram desenvolvidas duas aplicações para tele-imagiologia com esta
plataforma: repositório de imagens médicas e uma infraestrutura de
comunicações entre centros hospitalares. Finalmente, a arquitetura
desenvolvida é genérica e flexível permitindo facilmente a sua expansão para
outras áreas aplicacionais e outros serviços de cloud.Healthcare institutions resort largely, nowadays, to telemedicine in order to
support collaborative environments. In the medical imaging area, the huge
amount of medical volume data has increased over the past few years,
requiring high-performance infrastructures to provide services with required
quality. Computing devices and Internet access are now available anywhere
and at anytime, creating new opportunities to share and use online resources.
A tremendous amount of ubiquitous computational power and an
unprecedented number of Internet resources and services are used every day
as a normal commodity. This thesis presents a telemedicine service platform
over the Cloud that allows applications to store information and to communicate
easier, using any Internet cloud provider. With this platform, developers do not
concern where the resources will be deployed and the applications will not be
restricted to a specific cloud vendor. Two tele-imagiologic applications were
developed along with this platform: a medical imaging repository and an interinstitutional
communications infrastructure. Lastly, the architecture developed is
generic and flexible to expand to other application areas and cloud services
Arquiteturas federadas para integração de dados biomédicos
Doutoramento Ciências da ComputaçãoThe last decades have been characterized by a continuous adoption of
IT solutions in the healthcare sector, which resulted in the proliferation
of tremendous amounts of data over heterogeneous systems. Distinct
data types are currently generated, manipulated, and stored, in the
several institutions where patients are treated. The data sharing and an
integrated access to this information will allow extracting relevant
knowledge that can lead to better diagnostics and treatments.
This thesis proposes new integration models for gathering information
and extracting knowledge from multiple and heterogeneous biomedical
sources.
The scenario complexity led us to split the integration problem according
to the data type and to the usage specificity. The first contribution is a
cloud-based architecture for exchanging medical imaging services. It
offers a simplified registration mechanism for providers and services,
promotes remote data access, and facilitates the integration of
distributed data sources. Moreover, it is compliant with international
standards, ensuring the platform interoperability with current medical
imaging devices. The second proposal is a sensor-based architecture
for integration of electronic health records. It follows a federated
integration model and aims to provide a scalable solution to search and
retrieve data from multiple information systems. The last contribution is
an open architecture for gathering patient-level data from disperse and
heterogeneous databases. All the proposed solutions were deployed
and validated in real world use cases.A adoção sucessiva das tecnologias de comunicação e de informação
na área da saúde tem permitido um aumento na diversidade e na
qualidade dos serviços prestados, mas, ao mesmo tempo, tem gerado
uma enorme quantidade de dados, cujo valor científico está ainda por
explorar. A partilha e o acesso integrado a esta informação poderá
permitir a identificação de novas descobertas que possam conduzir a
melhores diagnósticos e a melhores tratamentos clínicos.
Esta tese propõe novos modelos de integração e de exploração de
dados com vista à extração de conhecimento biomédico a partir de
múltiplas fontes de dados.
A primeira contribuição é uma arquitetura baseada em nuvem para
partilha de serviços de imagem médica. Esta solução oferece um
mecanismo de registo simplificado para fornecedores e serviços,
permitindo o acesso remoto e facilitando a integração de diferentes
fontes de dados. A segunda proposta é uma arquitetura baseada em
sensores para integração de registos electrónicos de pacientes. Esta
estratégia segue um modelo de integração federado e tem como
objetivo fornecer uma solução escalável que permita a pesquisa em
múltiplos sistemas de informação. Finalmente, o terceiro contributo é
um sistema aberto para disponibilizar dados de pacientes num contexto
europeu. Todas as soluções foram implementadas e validadas em
cenários reais
A Recommender System Based on Cohorts’ Similarity
[Abstract]
Aiming to better understand the genetic and environmental associations of Alzheimer's disease, many clinical trials and scientific studies have been conducted. However, these studies are often based on a small number of participants. To address this limitation, there is an increasing demand of multi-cohorts studies, which can provide higher statistical power and clinical evidence. However, this data integration implies dealing with the diversity of cohorts structures and the wide variability of concepts. Moreover, discovering similar cohorts to extend a running study is typically a demanding task. In this paper, we present a recommendation system to allow finding similar cohorts based on profile interests. The method uses collaborative filtering mixed with context-based retrieval techniques to find relevant cohorts on scientific literature about Alzheimer's diseases. The method was validated in a set of 62 cohorts.National Science Foundation (Portugal); POCI-01-0145-FEDER-01638
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IMAGE-IN: Interactive web-based multidimensional 3D visualizer for multi-modal microscopy images
Advances in microscopy hardware and storage capabilities lead to increasingly larger multidimensional datasets. The multiple dimensions are commonly associated with space, time, and color channels. Since “seeing is believing”, it is important to have easy access to user-friendly visualization software. Here we present IMAGE-IN, an interactive web-based multidimensional (N-D) viewer designed specifically for confocal laser scanning microscopy (CLSM) and focused ion beam scanning electron microscopy (FIB-SEM) data, with the goal of assisting biologists in their visualization and analysis tasks and promoting digital work-flows. This new visualization platform includes intuitive multidimensional opacity fine-tuning, shading on/off, multiple blending modes for volume viewers, and the ability to handle multichannel volumetric data in volume and surface views. The software accepts a sequence of image files or stacked 3D images as input and offers a variety of viewing options ranging from 3D volume/surface rendering to multiplanar reconstruction approaches. We evaluate the performance by comparing the loading and rendering timings of a heterogeneous dataset of multichannel CLSM and FIB-SEM images on two devices with installed graphic cards, as well as comparing rendered image quality between ClearVolume (the ImageJ open-source desktop viewer), Napari (the Python desktop viewer), Imaris (the closed-source desktop viewer), and our proposed IMAGE-IN web viewer
DICOMization of Proprietary Files Obtained from Confocal, Whole-Slide, and FIB-SEM Microscope Scanners
The evolution of biomedical imaging technology is allowing the digitization of hundreds of glass slides at once. There are multiple microscope scanners available in the market including low-cost solutions that can serve small centers. Moreover, new technology is being researched to acquire images and new modalities are appearing in the market such as electron microscopy. This reality offers new diagnostics tools to clinical practice but emphasizes also the lack of multivendor system’s interoperability. Without the adoption of standard data formats and communications methods, it will be impossible to build this industry through the installation of vendor-neutral archives and the establishment of telepathology services in the cloud. The DICOM protocol is a feasible solution to the aforementioned problem because it already provides an interface for visible light and whole slide microscope imaging modalities. While some scanners currently have DICOM interfaces, the vast majority of manufacturers continue to use proprietary solutions. This article proposes an automated DICOMization pipeline that can efficiently transform distinct proprietary microscope images from CLSM, FIB-SEM, and WSI scanners into standard DICOM with their biological information maintained within their metadata. The system feasibility and performance were evaluated with fifteen distinct proprietary modalities, including stacked WSI samples. The results demonstrated that the proposed methodology is accurate and can be used in production. The normalized objects were stored through the standard communications in the Dicoogle open-source archive
IMAGE-IN: Interactive web-based multidimensional 3D visualizer for multi-modal microscopy images.
Advances in microscopy hardware and storage capabilities lead to increasingly larger multidimensional datasets. The multiple dimensions are commonly associated with space, time, and color channels. Since "seeing is believing", it is important to have easy access to user-friendly visualization software. Here we present IMAGE-IN, an interactive web-based multidimensional (N-D) viewer designed specifically for confocal laser scanning microscopy (CLSM) and focused ion beam scanning electron microscopy (FIB-SEM) data, with the goal of assisting biologists in their visualization and analysis tasks and promoting digital workflows. This new visualization platform includes intuitive multidimensional opacity fine-tuning, shading on/off, multiple blending modes for volume viewers, and the ability to handle multichannel volumetric data in volume and surface views. The software accepts a sequence of image files or stacked 3D images as input and offers a variety of viewing options ranging from 3D volume/surface rendering to multiplanar reconstruction approaches. We evaluate the performance by comparing the loading and rendering timings of a heterogeneous dataset of multichannel CLSM and FIB-SEM images on two devices with installed graphic cards, as well as comparing rendered image quality between ClearVolume (the ImageJ open-source desktop viewer), Napari (the Python desktop viewer), Imaris (the closed-source desktop viewer), and our proposed IMAGE-IN web viewer
Performance comparison of Findaures and Otsu’s thresholding method on simulated infected mouse bone tissue images (Accuracy, Precision, Sensitivity, and F1 Score) across four trials.
Performance comparison of Findaures and Otsu’s thresholding method on simulated infected mouse bone tissue images (Accuracy, Precision, Sensitivity, and F1 Score) across four trials.</p