Topic
DICOM
About: DICOM is a research topic. Over the lifetime, 3375 publications have been published within this topic receiving 35658 citations. The topic is also known as: Digital Imaging and Communications in Medicine.
Papers published on a yearly basis
Papers
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11 Nov 2010TL;DR: This work presents the implementation of a mobile system that enables electronic healthcare data storage, update and retrieval using Cloud Computing using Google's Android operating system and provides management of patient health records and medical images.
Abstract: Cloud Computing provides functionality for managing information data in a distributed, ubiquitous and pervasive manner supporting several platforms, systems and applications. This work presents the implementation of a mobile system that enables electronic healthcare data storage, update and retrieval using Cloud Computing. The mobile application is developed using Google's Android operating system and provides management of patient health records and medical images (supporting DICOM format and JPEG2000 coding). The developed system has been evaluated using the Amazon's S3 cloud service. This article summarizes the implementation details and presents initial results of the system in practice.
317 citations
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TL;DR: The purpose of this article is to review recent innovations on the process and application of 3D printed objects from medical imaging data.
293 citations
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TL;DR: The AEC systems available in modern CT scanners can contribute to a significant reduction in radiation exposure to the patient and the image noise becomes more uniform within any given scan.
Abstract: Background: Today, practically all computed tomography (CT) systems are delivered with automatic exposure control (AEC) systems operating with tube current modulation in three dimensions. Each of these systems has different specifications and operates somewhat differently.Purpose: To evaluate AEC systems from four different CT scanner manufacturers: General Electric (GE), Philips, Siemens, and Toshiba, considering their potential for reducing radiation exposure to the patient while maintaining adequate image quality.Material and Methods: The dynamics (adaptation along the longitudinal axis) of tube current modulation of each AEC system were investigated by scanning an anthropomorphic chest phantom using both 16- and 64-slice CT scanners from each manufacturer with the AEC systems activated and inactivated. The radiation dose was estimated using the parameters in the DICOM image information and image quality was evaluated based on image noise (standard deviation of CT numbers) calculated in 0.5 cm2 circula...
222 citations
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20 May 2008
TL;DR: This is the first Digital Imaging and Communications in Medicine (DICOM) book to introduce this complex imaging standard from a very practical point of view and is accompanied by an analysis of the most common pitfalls and problems associated with its implementation.
Abstract: This is the first Digital Imaging and Communications in Medicine (DICOM) book to introduce this complex imaging standard from a very practical point of view. It is aimed at a broad audience of radiologists, clinical administrators, information technologists, and digital medicine practitioners. It provides a gradual, down-to-earth introduction to DICOM and is accompanied by an analysis of the most common pitfalls and problems associated with its implementation. Whether you are running a teleradiology project or writing DICOM software, this book is for you; it will prepare you for any DICOM project or problem solving and will help you to take full advantage of this powerful tool.
220 citations
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29 Jan 2020TL;DR: A publicly available dataset containing k-space data as well as Digital Imaging and Communications in Medicine image data of knee images for accelerated MR image reconstruction using machine learning is presented.
Abstract: A publicly available dataset containing k-space data as well as Digital Imaging and Communications in Medicine image data of knee images for accelerated MR image reconstruction using machine learning is presented.
211 citations