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Specialty: Radiology
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Total 224 results found since Jan 2013.
Infervision unveils AI app, RSNA sessions
Chinese artificial intelligence (AI) software developer Infervision has released...Read more on AuntMinnie.comRelated Reading:
AI firm Infervision scores $47M in funding
Infervision debuts AI stroke screening software
AI developer Infervision adds to coffers
AI start-up eyes deep learning to aid imaging in China
Source: AuntMinnie.com Headlines - November 14, 2019 Category: Radiology Source Type: news
AI comparable to rads for interpreting wrist x-rays
An artificial intelligence (AI) deep-learning algorithm performs comparably...Read more on AuntMinnie.comRelated Reading:
Ultrasound can benefit daily rheumatology practice
Skip ultrasound for treatment decisions in rheumatoid arthritis
AI accurately estimates bone age on 3D hand MRI
AI can detect, localize fractures on wrist x-rays
Ultrasound imaging gauges muscle tightness after stroke
Source: AuntMinnie.com Headlines - March 17, 2020 Category: Radiology Source Type: news
Usefulness of deep learning-assisted identification of hyperdense MCA sign in acute ischemic stroke: comparison with readers ’ performance
ConclusionThe ability of DCNN to identify HMCAS is comparable with the diagnostic performance of neuroradiologists.
Source: Japanese Journal of Radiology - May 11, 2020 Category: Radiology Source Type: research
Double-contrast technique could boost MRI for cancer
A new double-contrast MRI technique in development could help the modality...Read more on AuntMinnie.comRelated Reading:
COVID-19 neuro findings marked by mental status, stroke
fMRI-based machine learning helps predict coma outcomes
ISMRM annual meeting goes virtual
MRI illuminates neurologic manifestations of COVID-19
MRI could help predict efficacy of stem cell therapy
Source: AuntMinnie.com Headlines - May 28, 2020 Category: Radiology Source Type: news
Fully automated quantification of left ventricular volumes and function in cardiac MRI: clinical evaluation of a deep learning-based algorithm
AbstractTo investigate the performance of a deep learning-based algorithm for fully automated quantification of left ventricular (LV) volumes and function in cardiac MRI. We retrospectively analysed MR examinations of 50 patients (74% men, median age 57 years). The most common indications were known or suspected ischemic heart disease, cardiomyopathies or myocarditis. Fully automated analysis of LV volumes and function was performed using a deep learning-based algorithm. The analysis was subsequently corrected by a senior cardiovascular radiologi st. Manual volumetric analysis was performed by two radiology trainees. Vol...
Source: The International Journal of Cardiovascular Imaging - July 15, 2020 Category: Radiology Source Type: research
Brain lesions on DWI-MRI linked to poor outcomes for some
Lesions that appear on diffusion-weighted imaging (DWI) MRI scans represent...Read more on AuntMinnie.comRelated Reading:
Deep-learning model detects cerebral microbleeds on MRI
Key MRI markers link vascular brain injury to health risks
5 risk factors help predict brain hemorrhage on CT
Combination of ultrasound, tPA may boost stroke treatment
CT guidance helps brain hemorrhage outcomes
Source: AuntMinnie.com Headlines - July 21, 2020 Category: Radiology Source Type: news
CT radiomics predicts esophageal cancer outcomes
Machine-learning models that assess both peritumoral and intratumoral radiomics...Read more on AuntMinnie.comRelated Reading:
PET radiomics tailor head/neck cancer treatment
CT radiomics can predict COVID-19 pneumonia outcomes
AI, radiomics can predict stroke treatment success
Can radiomics improve CT lung cancer screening?
AI can predict if COVID-19 patients will need ventilators
Source: AuntMinnie.com Headlines - September 11, 2020 Category: Radiology Source Type: news
Diverse Applications of Artificial Intelligence in Neuroradiology
Recent advances in artificial intelligence (AI) and deep learning (DL) hold promise to augment neuroimaging diagnosis for patients with brain tumors and stroke. Here, the authors review the diverse landscape of emerging neuroimaging applications of AI, including workflow optimization, lesion segmentation, and precision education. Given the many modalities used in diagnosing neurologic diseases, AI may be deployed to integrate across modalities (MR imaging, computed tomography, PET, electroencephalography, clinical and laboratory findings), facilitate crosstalk among specialists, and potentially improve diagnosis in patient...
Source: Neuroimaging Clinics - September 16, 2020 Category: Radiology Authors: Michael Tran Duong, Andreas M. Rauschecker, Suyash Mohan Source Type: research
An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1: Hemorrhagic Stroke Imaging and Triage
Publication date: Available online 17 September 2020Source: Neuroimaging Clinics of North AmericaAuthor(s): Rajiv Gupta, Sanjith Prahas Krishnam, Pamela W. Schaefer, Michael H. Lev, R. Gilberto Gonzalez
Source: Neuroimaging Clinics of North America - September 18, 2020 Category: Radiology Source Type: research
Artificial intelligence in stroke imaging: Current and future perspectives
Artificial intelligence (AI) is a fast-growing research area in computer science that aims to mimic cognitive processes through a number of techniques. Supervised machine learning, a subfield of AI, includes methods that can identify patterns in high-dimensional data using labeled ‘ground truth’ data and apply these learnt patterns to analyze, interpret, or make predictions on new datasets. Supervised machine learning has become a significant area of interest within the medical community. Radiology and neuroradiology in particular are especially well suited for applicatio n of machine learning due to the vast amount of...
Source: Clinical Imaging - September 19, 2020 Category: Radiology Authors: Vivek Yedavalli, Elizabeth Tong, Dann Martin, Kristen Yeom, Nils Forkert Tags: Artificial Intelligence Source Type: research
An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 2: Ischemic Stroke Imaging and Triage
Publication date: November 2020Source: Neuroimaging Clinics of North America, Volume 30, Issue 4Author(s): Rajiv Gupta, Sanjith Prahas Krishnam, Pamela W. Schaefer, Michael H. Lev, R. Gilberto Gonzalez
Source: Neuroimaging Clinics of North America - October 8, 2020 Category: Radiology Source Type: research
Machine learning boosts chest CT's performance
Machine learning-based CT texture analysis software improves reader accuracy...Read more on AuntMinnie.comRelated Reading:
AI can quantify hematoma in hemorrhagic stroke patients
Large study confirms value of CT lung cancer screening
CT radiation doses for COVID-19 patients vary widely
CT lung screening scans also work for bone density
CT lung screening program falls short in China
Source: AuntMinnie.com Headlines - November 18, 2020 Category: Radiology Source Type: news
Structural and functional connectivity of motor circuits after perinatal stroke: A machine learning study
Publication date: Available online 19 November 2020Source: NeuroImage: ClinicalAuthor(s): Helen L. Carlson, Brandon T. Craig, Alicia Hilderley, Jacquie Hodge, Deepthi Rajashekar, Pauline Mouches, Nils D. Forkert, Adam Kirton
Source: NeuroImage: Clinical - November 19, 2020 Category: Radiology Source Type: research
CT quantifies COVID-19 severity, ongoing conditions
Throughout this year's COVID-19 pandemic, chest CT has proven to be a valuable...Read more on AuntMinnie.comRelated Reading:
Deep learning gives a boost to CT image reconstruction
CO-RADS system helps clinicians assess COVID-19
Diabetes, hypertension boost COVID-19 stroke risk
Machine learning boosts chest CT's performance
COVID-19, AI, and dose reduction top RSNA's CT agenda
Source: AuntMinnie.com Headlines - November 30, 2020 Category: Radiology Source Type: news
Deep learning with MR helps monitor hydrocephalus in kids
An automated deep-learning method for MRI was highly accurate for assessing...Read more on AuntMinnie.comRelated Reading:
How good is the evidence supporting AI in radiology?
Arterys brings Avicenna AI stroke software on board
AI developer expands portfolio of cerebrovascular offerings
AI, COVID-19 imaging dominate RSNA 2020 so far
Deep learning distinguishes between Alzheimer's, iNPH
Source: AuntMinnie.com Headlines - December 2, 2020 Category: Radiology Source Type: news
