Nichols, Steven Laffin, Bruno Parisot, Charles
Published in
Journal of digital imaging
Alignment of DICOM (Digital Imaging and Communications in Medicine) capabilities among vendors is crucial to improve interoperability in the healthcare industry and advance medical imaging 2. However, a sustainable model for sharing DICOM samples is not available. To address this issue, Integrating the Healthcare Enterprise (IHE) has introduced the...
Yang, Yanfei Wang, Huidong Liu, Zhanyi Wang, Yanmei Han, Xiaole Jia, Yifan Pang, Jiaojiao Xie, Fei Yu, Dexin Zhang, Yang
...
Published in
iScience
Magnetocardiography (MCG) can be used to noninvasively measure the electrophysiological activity of myocardial cells. The high spatial resolution of magnetic source localization can precisely determine the location of cardiomyopathy, which is of great significance for the diagnosis and treatment of cardiovascular disease. To perform magnetic source...
Sulaksono, Nanang Adi, Kusworo Isnanto, dan Rizal
Published in
E3S Web of Conferences
Medical imaging is currently using artificial intelligence-based technologies to aid evaluate diagnostic information images, particularly in enforcing kidney stones. Artificial intelligence technology continues to develop, many studies show that deep learning is more widely used compared to traditional machine learning, so an Artificial intelligenc...
Kerkhof, Peter L M Tona, Francesco
Published in
Atherosclerosis
Asymptomatic atherosclerosis begins early in life and may progress in a sex-specific manner to become the major cause of cardiovascular morbidity and death. As diagnostic tools to evaluate atherosclerosis in the macrocirculation, we discuss imaging methods (in terms of computed tomography, positron emission tomography, intravascular ultrasound, mag...
Lahlouh, Mounir
L'imagerie médicale joue un rôle majeur dans le diagnostic de pathologies des vaisseaux cérébraux comme les anévrismes, les malformations artérioveineuses cérébrales (MAV) ou les sténoses. Elle intervient également dans les phases pré- et peropératoires du traitement endovasculaire en neuroradiologie interventionnelle. Cette technique, considérée c...
Soler Guiral, Ferran
[ES] La sencillez de adquisición de las radiografías simples de tórax, así como su gran utilidad en la detección de diversas patologías, las convierten en una de las pruebas más solicitadas en los servicios de urgencias hospitalarias. Sin embargo, la alta demanda de los servicios radiológicos hace inviable que todas ellas puedan ser revisadas e inf...
Kazi, Amaan Betko, Sage Salvi, Anish Menon, Prahlad G
Published in
Annals of biomedical engineering
The left atrial appendage (LAA) causes 91% of thrombi in atrial fibrillation patients, a potential harbinger of stroke. Leveraging computed tomography angiography (CTA) images, radiologists interpret the left atrium (LA) and LAA geometries to stratify stroke risk. Nevertheless, accurate LA segmentation remains a time-consuming task with high inter-...
Serra Gil, Jaime
[ES] Los sistemas de almacenamiento de imagen médica empleados en los hospitales (PACS) no han sido diseñados teniendo en cuenta la creación de herramientas analíticas o de aprendizaje automático, lo que hace que presenten ciertas limitaciones que dificultan el proceso de trabajo, dando lugar a que sea poco eficiente y automatizable. El auge del bi...
Vakalopoulou, Maria Christodoulidis, Stergios Burgos, Ninon Colliot, Olivier Lepetit, Vincent
Deep learning belongs to the broader family of machine learning methods and currently provides state-of-the-art performance in a variety of fields, including medical applications. Deep learning architectures can be categorized into different groups depending on their components. However, most of them share similar modules and mathematical formulati...
Silva Rincon, Santiago Smith
In order to gather sufficient sample size and representativity of clinical populations, the multi-centric analysis paradigm is often adopted for statistical and machine learning studies of biomedical data, particularly in the field of neuroimaging. Conventional multi-centric analysis paradigms are based on meta-analysis and mega-analysis, often in ...
