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Deep learning: its potential and challenges in radiology AI
June 26, 2018 by Jorrit Glastra
Up to a few years ago conventional image analysis was based on the careful handcrafting of features by humans that captured the relevant aspects of ...
3 Reasons why radiomics can revolutionize brain tumor diagnosis and prognosis
June 04, 2018 by Ory Six
The field of radiomics covers a range of methods aimed at the extraction of quantitative features from medical images, and linking these features to ...
How to make radiology AI cope with different scanners and settings?
May 02, 2018 by Annegreet van Opbroek
Segmentation of MRI and CT images into the available tissues and structures plays a crucial role in quantification, both in medical research and ...
How can AI help determine time of ischemic stroke onset?
April 11, 2018 by Willem Deserno
The prescribed moment to perform thrombolysis is within 3 to 4.5 hours after the onset of stroke (the guideline of the Dutch Neurology, Radiology and ...
The role of CT and MR in stroke patients
March 14, 2018 by Ory Six
Stroke is one of the most common causes of death in the western world causing more than 6 million deaths per year.1 Annually, almost 17 million ...
The Future of AI in Radiology and Medical Imaging: An Interview with Wiro Niessen
March 02, 2018 by Ory Six
Artificial intelligence (AI) continues to grow as machine learning expands its capabilities into new industries. At ECR, artificial intelligence was ...
Diagnosing Oligodendrogliomas: Can MRI Scans be as Reliable as a Genomic Profile?
November 06, 2017 by Ory Six
After a MRI or CT scan of a patient suffering from seizures and severe headaches, an invasive biopsy needs to be taken to determine with certainty ...
Detecting dementia: providing radiologists with more information in less time
October 26, 2017 by Ory Six
Different subtypes of dementia exist, with the most common form, which occurs in 50-70% of the cases, being Alzheimer’s Disease (AD). AD is ...
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