798 research outputs found
Use of a Thin-Section Archive and Enterprise 3-Dimensional Software for Long-Term Storage of Thin-Slice CT Data Sets—A Reviewers’ Response
Current developments in storage solutions, PACS, and client-server systems allow for 3D imaging at the desktop. This can be achieved together with full storage into PACS of all slices, including the very large thin-section CT datasets. This paper describes a possible setup, which has been in operation for several years now, in response to an article by Meenan et al. previously published in this journal (1)
The Reference Image Database to Evaluate Response to Therapy in Lung Cancer (RIDER) Project: A Resource for the Development of Change‐Analysis Software
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110105/1/cptclpt2008161.pd
Information Technologies for the Healthcare Delivery System
That modern healthcare requires information technology to be efficient and fully effective is evident if one spends any time observing the delivery of institutional health care. Consider the observation of a practitioner of the discipline, David M. Eddy, MD, PhD, voiced in Clinical Decision Making, JAMA 263:1265-75, 1990, . . .All confirm what would be expected from common sense: The complexity of modern medicine exceeds the inherent limitations of the unaided human mind. The goal of this thesis is to identify the technological factors that are required to enable a fully sufficient application of information technology (IT) to the modern institutional practice of medicine. Perhaps the epitome of healthcare IT is the fully integrated, fully electronic patient medical record. Although, in 1991 the Institute of Medicine called for such a record to be standard technology by 2001, it has still not materialized. The author will argue that some of the technology and standards that are pre-requisite for this achievement have now arrived, while others are still evolving to fully sufficient levels. The paper will concentrate primarily on the health care system in the United States, although much of what is contained is applicable to a large degree, around the world. The paper will illustrate certain of these pre-requisite IT factors by discussing the actual installation of a major health care computer system at the University of Rochester Medical Center (URMC) in Rochester, New York. This system is a Picture Archiving and Communications System (PACS). As the name implies, PACS is a system of capturing health care images in digital format, storing them and communicating them to users throughout the enterprise
Sequential slice object labeling in tomographic data via trajectory estimation
The increasing usage of volumetric imaging modalities, such as magnetic resonance imaging (MRI) and computed tomography (CT) in areas such as medicine and nondestructive evaluation (NDE) has placed a great importance on 3D visualization techniques. This growth of volume data in the form of cross sections has created the need for object labeling in volume data sets for 3D visualization. A sequential, slice-to-slice approach is proposed that is less computational and memory intensive than 3D connected-component labeling while achieving better results than the 2D overlap sequential processing approach. Labeling occurs while tracking each object through the 3D volume via updated trajectory approximation.
This thesis is motivated by the desire to develop a labeling technique that captures key aspects of the human visual approach to the task. The proposed approach, while labeling 3D data, also provides a computationally efficient method by sequential processing of 2D slices instead of the whole 3D volume at once. Additionally, the proposed trajectory tracking approach performs correctly in many cases where current 2D sequential labeling techniques fail.
Trajectory tracking for labeling is a new approach, representing the 3D objects as curves and performing 3D curve tracing to label the approximate trajectories of the objects. The labeled trajectories are then mapped back to the 3D objects to complete the labeling process. Development of the proposed labeling approach is discussed while multiple examples are presented. These examples are used to illustrate that the proposed approach performs correctly where the current overlap approach fails; examples are also used to show that the behavior of the proposed approach parallels that of the typical human approach to object tracking
Recuperação de informação multimodal em repositórios de imagem médica
The proliferation of digital medical imaging modalities in hospitals and other
diagnostic facilities has created huge repositories of valuable data, often
not fully explored. Moreover, the past few years show a growing trend
of data production. As such, studying new ways to index, process and
retrieve medical images becomes an important subject to be addressed by
the wider community of radiologists, scientists and engineers. Content-based
image retrieval, which encompasses various methods, can exploit the visual
information of a medical imaging archive, and is known to be beneficial to
practitioners and researchers. However, the integration of the latest systems
for medical image retrieval into clinical workflows is still rare, and their
effectiveness still show room for improvement.
This thesis proposes solutions and methods for multimodal information
retrieval, in the context of medical imaging repositories. The major
contributions are a search engine for medical imaging studies supporting
multimodal queries in an extensible archive; a framework for automated
labeling of medical images for content discovery; and an assessment and
proposal of feature learning techniques for concept detection from medical
images, exhibiting greater potential than feature extraction algorithms that
were pertinently used in similar tasks. These contributions, each in their
own dimension, seek to narrow the scientific and technical gap towards
the development and adoption of novel multimodal medical image retrieval
systems, to ultimately become part of the workflows of medical practitioners,
teachers, and researchers in healthcare.A proliferação de modalidades de imagem médica digital, em hospitais,
clínicas e outros centros de diagnóstico, levou à criação de enormes
repositórios de dados, frequentemente não explorados na sua totalidade.
Além disso, os últimos anos revelam, claramente, uma tendência para o
crescimento da produção de dados. Portanto, torna-se importante estudar
novas maneiras de indexar, processar e recuperar imagens médicas, por
parte da comunidade alargada de radiologistas, cientistas e engenheiros. A
recuperação de imagens baseada em conteúdo, que envolve uma grande
variedade de métodos, permite a exploração da informação visual num
arquivo de imagem médica, o que traz benefícios para os médicos e
investigadores. Contudo, a integração destas soluções nos fluxos de trabalho
é ainda rara e a eficácia dos mais recentes sistemas de recuperação de
imagem médica pode ser melhorada.
A presente tese propõe soluções e métodos para recuperação de informação
multimodal, no contexto de repositórios de imagem médica. As contribuições
principais são as seguintes: um motor de pesquisa para estudos de imagem
médica com suporte a pesquisas multimodais num arquivo extensível; uma
estrutura para a anotação automática de imagens; e uma avaliação e
proposta de técnicas de representation learning para deteção automática de
conceitos em imagens médicas, exibindo maior potencial do que as técnicas
de extração de features visuais outrora pertinentes em tarefas semelhantes.
Estas contribuições procuram reduzir as dificuldades técnicas e científicas
para o desenvolvimento e adoção de sistemas modernos de recuperação de
imagem médica multimodal, de modo a que estes façam finalmente parte
das ferramentas típicas dos profissionais, professores e investigadores da área
da saúde.Programa Doutoral em Informátic
Effect of curing conditions and harvesting stage of maturity on Ethiopian onion bulb drying properties
The study was conducted to investigate the impact of curing conditions and harvesting stageson the drying quality of onion bulbs. The onion bulbs (Bombay Red cultivar) were harvested at three harvesting stages (early, optimum, and late maturity) and cured at three different temperatures (30, 40 and 50 oC) and relative humidity (30, 50 and 70%). The results revealed that curing temperature, RH, and maturity stage had significant effects on all measuredattributesexcept total soluble solids
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