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CT Image-Guided Electrical Impedance Tomography for Medical Imaging
This study presents a computed tomography (CT) image-guided electrical impedance tomography (EIT) method for medical imaging. CT is a robust imaging modality for accurately reconstructing the density structure of the region being scanned. EIT can detect electrical impedance abnormalities to which CT scans may be insensitive, but the poor spatial resolution of EIT is a major concern for medical applications. A cross-gradient method has been introduced for oil and gas exploration to jointly invert multiple geophysical datasets associated with different medium properties in the same geological structure. In this study, we dev...
Source: IEE Transactions on Medical Imaging - May 31, 2020 Category: Biomedical Engineering Source Type: research

Three-Dimensional Printing in Medical and Allied Health Practice: A Literature Review
Three-dimensional printing (3DP), first implemented as nonmedical science in engineering in 1986, has grown immensely in its current integration into the health care field. Three-dimensional printing may possibly lower health care costs and promote a higher quality of patient care. The implementation of 3DP in conjunction with postprocessing computed tomography and magnetic resonance imaging has opened up avenues for the medical and allied health fields including prosthetics, surgery, radiation therapy, medical dosimetry, biomedical research, and organ transplantation.
Source: Journal of Medical Imaging and Radiation Sciences - June 29, 2020 Category: Radiology Authors: Suzzette Renee Spencer, Lynette Kay Watts Tags: Review Article Source Type: research

The EU medical device regulation: Implications for artificial intelligence-based medical device software in medical physics
Of all available health data, medical images – such as those obtained through x-rays, computed tomography, magnetic resonance, nuclear medicine, and ultrasound examinations – possibly constitute the most interesting ones for artificial intelligence (AI) applications. Artificial intelligence is expected to soon play a key role in diagnostic imaging [1,2], radiation therapy [3,4] and medical physics in general. It has already been demonstrated to successfully improve image quality [1], decrease radiation dosage [5,6], assign label types and identify pathology locations [7–13], create and optimize protocols [14], accura...
Source: Physica Medica: European Journal of Medical Physics - March 1, 2021 Category: General Medicine Authors: R. Beckers, Z. Kwade, F. Zanca Source Type: research

A review of deep learning based methods for medical image multi-organ segmentation
Medical image segmentation is one of the most important medical image analysis tasks. It has a wide range of applications in imaging systems such as microscopy, X-ray, ultrasound, computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography (PET). Medical image segmentation plays an essential role in radiotherapy, which is the standard care for certain cancers [1]. The success of radiotherapy depends highly on accurate irradiation to the target and sparing of organs-at-risk (OARs) [2,3].
Source: Physica Medica: European Journal of Medical Physics - May 13, 2021 Category: General Medicine Authors: Yabo Fu, Yang Lei, Tonghe Wang, Walter J. Curran, Tian Liu, Xiaofeng Yang Tags: Review paper Source Type: research

National diagnostic reference levels: What they are, why we need them and what ’s next
AbstractDiagnostic reference levels (DRLs) are an optimisation tool for medical imaging procedures using ionising radiation. They give an indication of the expected radiation dose received by an average-sized patient undergoing a given imaging procedure. Comparison of typical (median) exposure levels for common imaging procedures with DRLs helps imaging facilities identify procedures that may be amenable to further optimisation. Undertaking comparisons with published DRLs is a requirement for medical imaging facilities under the Code for Radiation Protection in Medical Exposure and for their access to Medicare rebates unde...
Source: Journal of Medical Imaging and Radiation Oncology - March 4, 2022 Category: Radiology Authors: Peter Thomas Tags: Medical Imaging –Review Article Source Type: research

A survey of machine learning-based methods for COVID-19 medical image analysis
AbstractThe ongoing COVID-19 pandemic caused by the SARS-CoV-2 virus has already resulted in 6.6 million deaths with more than 637 million people infected after only 30 months since the first occurrences of the disease in December 2019. Hence, rapid and accurate detection and diagnosis of the disease is the first priority all over the world. Researchers have been working on various methods for COVID-19 detection and as the disease infects lungs, lung image analysis has become a popular research area for detecting the presence of the disease. Medical images from chest X-rays (CXR), computed tomography (CT) images, and lung ...
Source: Medical and Biological Engineering and Computing - May 13, 2023 Category: Biomedical Engineering Source Type: research

5 Diagnostic radiography and reach back capability in the remotely deployed environment; a summary from op newcombe rotation 3
Diagnostics remains to be an important and vital capability of any deployed field hospital or surgical team, particularly for teams that find themselves deployed in the most remote locations, such as Mali. The DRGo gives the British military a portable radiography solution. Completely digital, it provides an instantaneous X-ray for clinicians to review. A 6-month period between Dec 21 and Jun 22 saw 29 full X-ray examinations completed with a 50% split between those patients being referred for imaging in the firm base and those referred whilst out on patrol. With no deployed radiologists on the ground, the ability to obtai...
Source: Journal of the Royal Army Medical Corps - May 22, 2023 Category: General Medicine Authors: Sgt Jessica Bailey Tags: Abstracts from the Mali Medical Conference Source Type: research

3-D Images Created By Imaging Specialists To Aid Surgeons
University of Notre Dame researchers have successfully created three-dimensional anatomical models from CT scans using 3-D printing technology, a process that holds promise for medical professionals and their patients. A paper by the researchers, "3D Printing of Preclinical X-ray Computed Tomographic Data Sets," was published in the Journal of Visualized Experiments this week. The strategy was initiated last spring by then-freshman Evan Doney, a Glynn Family Honors student in the laboratory of W. Matthew Leevy, research assistant professor at the Notre Dame Integrated Imaging Facility...
Source: Health News from Medical News Today - April 5, 2013 Category: Consumer Health News Tags: Medical Devices / Diagnostics Source Type: news

Interactive Medical Image Segmentation Using PDE Control of Active Contours
Segmentation of injured or unusual anatomic structures in medical imagery is a problem that has continued to elude fully automated solutions. In this paper, the goal of easy-to-use and consistent interactive segmentation is transformed into a control synthesis problem. A nominal level set partial differential equation (PDE) is assumed to be given; this open-loop system achieves correct segmentation under ideal conditions, but does not agree with a human expert's ideal boundary for real image data. Perturbing the state and dynamics of a level set PDE via the accumulated user input and an observer-like system leads to desira...
Source: IEE Transactions on Medical Imaging - October 30, 2013 Category: Biomedical Engineering Source Type: research

Feasibility study of propagation-based phase-contrast X-ray lung imaging on the Imaging and Medical beamline at the Australian Synchrotron
This study aimed to measure the capabilities of PB-PCXI on IMBL for imaging small animal lungs to study lung disease. The feasibility of combining this technique with computed tomography for three-dimensional imaging and X-ray velocimetry for studies of airflow and non-invasive lung function testing was also investigated. Detailed analysis of the role of the effective source size and sample-to-detector distance on lung image contrast was undertaken as well as phase retrieval for sample volume analysis. Results showed that PB-PCXI of lung phantoms and mouse lungs produced high-contrast images, with successful computed tomog...
Source: Journal of Synchrotron Radiation - January 30, 2014 Category: Physics Authors: Murrie, R.P.Stevenson, A.W.Morgan, K.S.Fouras, A.Paganin, D.M.Siu, K.K.W. Tags: X-ray phase contrast lung propagation-based medical imaging velocimetry computed tomography Australian Synchrotron research papers Source Type: research

A graph-based approach for the retrieval of multi-modality medical images
Graphical abstract: Highlights: Abstract: In this paper, we address the retrieval of multi-modality medical volumes, which consist of two different imaging modalities, acquired sequentially, from the same scanner. One such example, positron emission tomography and computed tomography (PET-CT), provides physicians with complementary functional and anatomical features as well as spatial relationships and has led to improved cancer diagnosis, localisation, and staging.The challenge of multi-modality volume retrieval for cancer patients lies in representing the complementary geometric and topologic attributes between tumours a...
Source: Medical Image Analysis - December 9, 2013 Category: Radiology Authors: Ashnil Kumar, Jinman Kim, Lingfeng Wen, Michael Fulham, Dagan Feng Source Type: research

Written Observations as a Part of Computed Tomography Angiography Post Processing by Medical Radiation Technologists: A Pilot Project
Abstract: Background: A facility faced a local backlog of computed tomography angiography (CTA) results. During post processing, technologists review the CTA images and may consider pathology demonstrated. This is an excellent scenario for a clinical observation as part of an advanced practice role.Method and Materials: Five hundred seventeen CTA examinations were performed during the project period. The medical radiation technologist post processed and included observations for 78 CTA examinations. The impact on the timely release of results was considered. The analysis compared the time frame from actual scan completion ...
Source: Journal of Medical Imaging and Radiation Sciences - March 1, 2014 Category: Radiology Authors: Melanie W. Hilkewich Tags: Research Articles Source Type: research

Dual adaptive statistical approach for quantitative noise reduction in photon-counting medical imaging: application to nuclear medicine images.
Abstract Noise reduction in photon-counting images remains challenging, especially at low count levels. We have developed an original procedure which associates two complementary filters using a Wiener-derived approach. This approach combines two statistically adaptive filters into a dual-weighted (DW) filter. The first one, a statistically weighted adaptive (SWA) filter, replaces the central pixel of a sliding window with a statistically weighted sum of its neighbors. The second one, a statistical and heuristic noise extraction (extended) (SHINE-Ext) filter, performs a discrete cosine transformation (DCT) using s...
Source: Medical Physics - May 26, 2015 Category: Physics Authors: Hannequin PP Tags: Phys Med Biol Source Type: research

Large Margin Local Estimate With Applications to Medical Image Classification
Medical images usually exhibit large intra-class variation and inter-class ambiguity in the feature space, which could affect classification accuracy. To tackle this issue, we propose a new Large Margin Local Estimate (LMLE) classification model with sub-categorization based sparse representation. We first sub-categorize the reference sets of different classes into multiple clusters, to reduce feature variation within each subcategory compared to the entire reference set. Local estimates are generated for the test image using sparse representation with reference subcategories as the dictionaries. The similarity between the...
Source: IEE Transactions on Medical Imaging - June 1, 2015 Category: Biomedical Engineering Source Type: research

Medical News Today: 'No evidence that CT scans, X-rays cause cancer'
Researchers say there is no proof low-dose radiation from medical imaging causes cancer and urge we throw out the old, unproven theoretical model that makes people think otherwise.
Source: Health News from Medical News Today - February 4, 2016 Category: Consumer Health News Tags: Cancer / Oncology Source Type: news