Linking Whole-Slide Microscope Images with DICOM by Using JPEG2000 Interactive Protocol

The use of digitized histopathologic specimens (also known as whole-slide images (WSIs)) in clinical medicine requires compatibility with the Digital Imaging and Communications in Medicine (DICOM) standard. Unfortunately, WSIs usually exceed DICOM image object size limit, making it impossible to store and exchange them in a straightforward way. Moreover, transmitting the entire DICOM image for viewing is ineffective for WSIs. With the JPEG2000 Interactive Protocol (JPIP), WSIs can be linked with DICOM by transmitting image data over an auxiliary connection, apart from patient data. In this study, we explored the feasibility of using JPIP to link JPEG2000 WSIs with a DICOM-based Picture Archiving and Communications System (PACS). We first modified an open-source DICOM library by adding support for JPIP as described in the existing DICOM Supplement 106. Second, the modified library was used as a basis for a software package (JVSdicom), which provides a proof-of-concept for a DICOM client–server system that can transmit patient data, conventional DICOM imagery (e.g., radiological), and JPIP-linked JPEG2000 WSIs. The software package consists of a compression application (JVSdicom Compressor) for producing DICOM-compatible JPEG2000 WSIs, a DICOM PACS server application (JVSdicom Server), and a DICOM PACS client application (JVSdicom Workstation). JVSdicom is available for free from our Web site (http://jvsmicroscope.uta.fi/), which also features a public JVSdicom Server, containing example X-ray images and histopathology WSIs of breast cancer cases. The software developed indicates that JPEG2000 and JPIP provide a well-working solution for linking WSIs with DICOM, requiring only minor modifications to current DICOM standard specification

Biotieteen ohjelmistoviitekehysvaihtoehdot niukkaresurssisessa ympäristössä

Feature rich applications need to be delivered rapidly given the lean structure of many businesses today. Recently the number of available customizable existing software solutions has increased, enabling even small development teams to deliver complex solutions. However, small development teams still face serious risk of failure if unexpected limitations in modifiable off-the-shelf software prevent sustainable solution to business problems. This thesis introduces a new method for evaluating available customizable existing software in the context of a small development team. As a real-life example a complex whole slide imaging feature is developed into web-based life sciences research application. The introduced evaluation method is used for evaluating different implementation approaches and different whole slide imaging solutions. Finally one solution is picked and integrated with the research application and the suitability of the evaluation method is evaluated. The evaluation method introduced in this thesis helps utilizing small development teams’ limited resources to build complex software. The method can be generalized to be used to any development teams use, regardless the team’s size and to any software project, regardless the nature of the software.Monien yristysalojen luonne vaatii, että sovelluksia täytyy toimittaa aina vain nopeammin tinkimättä ohjelmiston ominaisuuksien määrästä. Viimeaikainen valmiiden muokattavissa olevien ohjelmistoratkaisujen määrän kasvu on mahdollistanut pienehköjen kehitystiimien toimittaa monimutkaisia ohjelmistojaratkaisuja, käyttäen hyväksi jo olemassa olevia ohjelmistoratkaisuja. Pienet ohjelmistokehitystiimit ottavat kuitenkin riskin, sillä muokattavissa olevat valmiit ohjelmistoratkaisut saattavat sisältää odottamattomia rajoitteita, jotka estävät kestävien ohjelmistoratkaisujen kehittämisen. Tässä opinnäytetyössä esitellään pienille ohjelmistokehitystiimeille sopivaa uutta arviointimenetelmää, jota käytetään arvioimaan valmiita muokattavissa olevia ohjelmistoratkaisuja. Opinnäytetyön esimerkkitapauksessa toteutetaan virtuaalimikroskopiaominaisuus olemassa olevaan verkkopohjaiseen biotieteiden tutkimussovellukseen. Esitettyä arviontimenetelmää käytetään erilaisten ohjelmistokehitystapojen sekä valmiiden virtuaalimikrosopiaohjelmistojen arvioimiseen. Lopuksi yksi ohjelmistoratkaisuista valitaan ja integroidaan tutkimussovelluksen kanssa sekä arviointimenetelmä sopivuus arvioidaan. Tässä opinnäytetyössä esitetty arviointimenetelmä auttaa hyödyntämään pienten ohjelmistokehitystiimien rajoitettuja resursseja monimutkaisen ohjelmistojen rakentamisessa. Arviointimenetelmä voidaan myös yleistää minkä tahansa ohjelmistotiimin käyttöön tiimin koosta riippumatta sekä minkä tahansa ohjelmistoprojektin käyttöön välittämättä ohjelmiston luonteesta

Métodos computacionais para otimização de desempenho em redes de imagem médica

Over the last few years, the medical imaging has consolidated its position as a major mean of clinical diagnosis. The amount of data generated by the medical imaging practice is increasing tremendously. As a result, repositories are turning into rich databanks of semi-structured data related to patients, ailments, equipment and other stakeholders involved in the medical imaging panorama. The exploration of these repositories for secondary uses of data promises to elevate the quality standards and efficiency of the medical practice. However, supporting these advanced usage scenarios in traditional institutional systems raises many technical challenges that are yet to be overcome. Moreover, the reported poor performance of standard protocols opened doors to the general usage of proprietary solutions, compromising the interoperability necessary for supporting these advanced scenarios. This thesis has researched, developed, and now proposes a series of computer methods and architectures intended to maximize the performance of multi-institutional medical imaging environments. The methods are intended to improve the performance of standard protocols for medical imaging content discovery and retrieval. The main goal is to use them to increase the acceptance of vendor-neutral solutions through the improvement of their performance. Moreover, it intends to promote the adoption of such standard technologies in advanced scenarios that are still a mirage nowadays, such as clinical research or data analytics directly on top of live institutional repositories. Finally, these achievements will facilitate the cooperation between healthcare institutions and researchers, resulting in an increment of healthcare quality and institutional efficiency.As diversas modalidades de imagem médica têm vindo a consolidar a sua posição dominante como meio complementar de diagnóstico. O número de procedimentos realizados e o volume de dados gerados aumentou significativamente nos últimos anos, colocando pressão nas redes e sistemas que permitem o arquivo e distribuição destes estudos. Os repositórios de estudos imagiológicos são fontes de dados ricas contendo dados semiestruturados relacionados com pacientes, patologias, procedimentos e equipamentos. A exploração destes repositórios para fins de investigação e inteligência empresarial, tem potencial para melhorar os padrões de qualidade e eficiência da prática clínica. No entanto, estes cenários avançados são difíceis de acomodar na realidade atual dos sistemas e redes institucionais. O pobre desempenho de alguns protocolos standard usados em ambiente de produção, conduziu ao uso de soluções proprietárias nestes nichos aplicacionais, limitando a interoperabilidade de sistemas e a integração de fontes de dados. Este doutoramento investigou, desenvolveu e propõe um conjunto de métodos computacionais cujo objetivo é maximizar o desempenho das atuais redes de imagem médica em serviços de pesquisa e recuperação de conteúdos, promovendo a sua utilização em ambientes de elevados requisitos aplicacionais. As propostas foram instanciadas sobre uma plataforma de código aberto e espera-se que ajudem a promover o seu uso generalizado como solução vendor-neutral. As metodologias foram ainda instanciadas e validadas em cenários de uso avançado. Finalmente, é expectável que o trabalho desenvolvido possa facilitar a investigação em ambiente hospitalar de produção, promovendo, desta forma, um aumento da qualidade e eficiência dos serviços.Programa Doutoral em Engenharia Informátic

Virtual reality for 3D histology: multi-scale visualization of organs with interactive feature exploration

Virtual reality (VR) enables data visualization in an immersive and engaging manner, and it can be used for creating ways to explore scientific data. Here, we use VR for visualization of 3D histology data, creating a novel interface for digital pathology. Our contribution includes 3D modeling of a whole organ and embedded objects of interest, fusing the models with associated quantitative features and full resolution serial section patches, and implementing the virtual reality application. Our VR application is multi-scale in nature, covering two object levels representing different ranges of detail, namely organ level and sub-organ level. In addition, the application includes several data layers, including the measured histology image layer and multiple representations of quantitative features computed from the histology. In this interactive VR application, the user can set visualization properties, select different samples and features, and interact with various objects. In this work, we used whole mouse prostates (organ level) with prostate cancer tumors (sub-organ objects of interest) as example cases, and included quantitative histological features relevant for tumor biology in the VR model. Due to automated processing of the histology data, our application can be easily adopted to visualize other organs and pathologies from various origins. Our application enables a novel way for exploration of high-resolution, multidimensional data for biomedical research purposes, and can also be used in teaching and researcher training

JPIP proxy server with prefetching strategies based on user-navigation model and semantic map

The efficient transmission of large resolution images and, in particular, the interactive transmission of images in a client-server scenario, is an important aspect for many applications. Among the current image compression standards, JPEG2000 excels for its interactive transmission capabilities. In general, three mechanisms are employed to optimize the transmission of images when using the JPEG2000 Interactive Protocol (JPIP): 1) packet re-sequencing at the server; 2) prefetching at the client; and 3) proxy servers along the network infrastructure. To avoid the congestion of the network, prefetching mechanisms are not commonly employed when many clients within a local area network (LAN) browse images from a remote server. Aimed to maximize the responsiveness of all the clients within a LAN, this work proposes the use of prefetching strategies at the proxy server -rather than at the clients. The main insight behind the proposed prefetching strategies is a user-navigation model and a semantic map that predict the future requests of the clients. Experimental results indicate that the introduction of these strategies into a JPIP proxy server enhances the browsing experience of the end-users notably

Efficient interaction with large medical imaging databases

Everyday, a wide quantity of hospitals and medical centers around the world are producing large amounts of imaging content to support clinical decisions, medical research, and education. With the current trend towards Evidence-based medicine, there is an increasing need of strategies that allow pathologists to properly interact with the valuable information such imaging repositories host and extract relevant content for supporting decision making. Unfortunately, current systems are very limited at providing access to content and extracting information from it because of different semantic and computational challenges. This thesis presents a whole pipeline, comprising 3 building blocks, that aims to to improve the way pathologists and systems interact. The first building block consists in an adaptable strategy oriented to ease the access and visualization of histopathology imaging content. The second block explores the extraction of relevant information from such imaging content by exploiting low- and mid-level information obtained from from morphology and architecture of cell nuclei. The third block aims to integrate high-level information from the expert in the process of identifying relevant information in the imaging content. This final block not only attempts to deal with the semantic gap but also to present an alternative to manual annotation, a time consuming and prone-to-error task. Different experiments were carried out and demonstrated that the introduced pipeline not only allows pathologist to navigate and visualize images but also to extract diagnostic and prognostic information that potentially could support clinical decisions.Resumen: Diariamente, gran cantidad de hospitales y centros médicos de todo el mundo producen grandes cantidades de imágenes diagnósticas para respaldar decisiones clínicas y apoyar labores de investigación y educación. Con la tendencia actual hacia la medicina basada en evidencia, existe una creciente necesidad de estrategias que permitan a los médicos patólogos interactuar adecuadamente con la información que albergan dichos repositorios de imágenes y extraer contenido relevante que pueda ser empleado para respaldar la toma de decisiones. Desafortunadamente, los sistemas actuales son muy limitados en cuanto al acceso y extracción de contenido de las imágenes debido a diferentes desafíos semánticos y computacionales. Esta tesis presenta un marco de trabajo completo para patología, el cual se compone de 3 bloques y tiene como objetivo mejorar la forma en que interactúan los patólogos y los sistemas. El primer bloque de construcción consiste en una estrategia adaptable orientada a facilitar el acceso y la visualización del contenido de imágenes histopatológicas. El segundo bloque explora la extracción de información relevante de las imágenes mediante la explotación de información de características visuales y estructurales de la morfología y la arquitectura de los núcleos celulares. El tercer bloque apunta a integrar información de alto nivel del experto en el proceso de identificación de información relevante en las imágenes. Este bloque final no solo intenta lidiar con la brecha semántica, sino que también presenta una alternativa a la anotación manual, una tarea que demanda mucho tiempo y es propensa a errores. Se llevaron a cabo diferentes experimentos que demostraron que el marco de trabajo presentado no solo permite que el patólogo navegue y visualice imágenes, sino que también extraiga información de diagnóstico y pronóstico que potencialmente podría respaldar decisiones clínicas.Doctorad

Virtual reality for 3D histology: multi-scale visualization of organs with interactive feature exploration

Background Virtual reality (VR) enables data visualization in an immersive and engaging manner, and it can be used for creating ways to explore scientific data. Here, we use VR for visualization of 3D histology data, creating a novel interface for digital pathology to aid cancer research. Methods Our contribution includes 3D modeling of a whole organ and embedded objects of interest, fusing the models with associated quantitative features and full resolution serial section patches, and implementing the virtual reality application. Our VR application is multi-scale in nature, covering two object levels representing different ranges of detail, namely organ level and sub-organ level. In addition, the application includes several data layers, including the measured histology image layer and multiple representations of quantitative features computed from the histology. Results In our interactive VR application, the user can set visualization properties, select different samples and features, and interact with various objects, which is not possible in the traditional 2D-image view used in digital pathology. In this work, we used whole mouse prostates (organ level) with prostate cancer tumors (sub-organ objects of interest) as example cases, and included quantitative histological features relevant for tumor biology in the VR model. Conclusions Our application enables a novel way for exploration of high-resolution, multidimensional data for biomedical research purposes, and can also be used in teaching and researcher training. Due to automated processing of the histology data, our application can be easily adopted to visualize other organs and pathologies from various origins.</p