Medical Imaging Physics

Hendee, William R.; Ritenour, E. Russell

doi:10.1002/0471221155

Cited by 298 publications

(153 citation statements)

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“…The effect of missing data (i.e., projections) in the measured sinogram, caused by a possible detector malfunction during image acquisition, on the reconstructed image has been also included in the website. During reconstruction, the developed application performs common methods of image and system quality control of the simulated tomographic system, so that the user can compare the result of different geometries and reconstruction parameters both visually and quantitatively [27,29].…”

Section: Reconstruction Methodsmentioning

confidence: 99%

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A Web Simulation of Medical Image Reconstruction and Processing as an Educational Tool

et al. 2014

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Web educational resources integrating interactive simulation tools provide students with an in-depth understanding of the medical imaging process. The aim of this work was the development of a purely Web-based, open access, interactive application, as an ancillary learning tool in graduate and postgraduate medical imaging education, including a systematic evaluation of learning effectiveness. The pedagogic content of the educational Web portal was designed to cover the basic concepts of medical imaging reconstruction and processing, through the use of active learning and motivation, including learning simulations that closely resemble actual tomographic imaging systems. The user can implement image reconstruction and processing algorithms under a single user interface and manipulate various factors to understand the impact on image appearance. A questionnaire for pre-and post-training self-assessment was developed and integrated in the online application. The developed Web-based educational application introduces the trainee in the basic concepts of imaging through textual and graphical information and proceeds with a learning-by-doing approach. Trainees are encouraged to participate in a pre-and post-training questionnaire to assess their knowledge gain. An initial feedback from a group of graduate medical students showed that the developed course was considered as effective and well structured. An e-learning application on medical imaging integrating interactive simulation tools was developed and assessed in our institution.

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Section: Reconstruction Methodsmentioning

confidence: 99%

“…In general, the most important factors associated with medical image quality are noise, spatial resolution, and contrast [29]. A common way to quantify the level of noise in an image is to estimate the SNR.…”

Section: Image-quality Assessmentmentioning

confidence: 99%

A Web Simulation of Medical Image Reconstruction and Processing as an Educational Tool

et al. 2014

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“…Two major contributions exist to explain medical imaging noise: the acquisition noise and the physiological noise. The acquisition noise can be identified as and sometimes reduced to physical noise meaning that it depends on the physical method of acquisition (Hendee & Ritenour, 2002;Vasilescu, 2005), for example, MRI noise caused by MRI machines. For the physiological noise, there are three main contributions : the respiratory cycle, the cardiac cycle and the scattered noise mainly due to physiological liquid action.…”

Section: Noise Problemmentioning

confidence: 99%

Image Processing on MR Brain Images Using Social Spiders

Moussa¹,

Beurton-Aimar²,

Desbarats³

2011

Multi-Agent Systems - Modeling, Control, Programming, Simulations and Applications

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“…After these first steps, radiology evolved at a good rate until World War II. The intense use of x-rays during the Second World War, and the arrival of the digital computer and new modalities such as ultrasound and magnetic resonance have triggered a boom in diagnostic imaging techniques in the past years (Hendee & Ritenour, 2002). Digital imaging techniques have been in use since the 1970s after the clinical acceptance of Computer Tomography (CT scanner).…”

Section: Introductionmentioning

confidence: 99%