AI in radiology

 10 tips to maximize your visit to healthcare conferences February 23, 2023 by Ory Six The calendar of 2023 healthcare conferences has already started and its first big swing is happening in March with some of the biggest European ... Read Post
Quantib: 10 years of AI software development in radiology January 31, 2023 by Marta Sánchez-Molero Veguillas Recently, we turned 10 years old. With that, it is fair to say that the team has grown, learned, and evolved. The field of radiology, or medical ... Read Post
Deep learning applications in radiology: a deep dive on image segmentation October 25, 2022 by Pim Moeskops Organ volumes, tumor dimensions, size of lymph nodes - these are some examples of measures that provide valuable information for radiologists to use ... Read Post
Clinical implementation of AI in radiology: facing the challenges August 30, 2022 by Tiago Beck Radiology is facing multiple challenges. A global shortage of radiologists1, an increasing population, and an increasing demand for imaging and ... Read Post
Deep learning applications in radiology: a deep dive on classification May 31, 2022 by Valerio Fortunati A few years ago the FDA cleared the first medical software using deep learning (DL) networks. This opened the door to many more companies applying ... Read Post
Productivity in Radiology February 24, 2022 by Almar van Loon In the era of preventive healthcare, early diagnosis and non-invasive treatments are the key to success. As a result, the imaging community has ... Read Post
How to evaluate AI radiology algorithms January 20, 2022 by Jim Tol The number of AI solutions in healthcare and specifically radiology, has increased strongly in the past years. However, the more options we are ... Read Post
A trick to get the best performance from an AI radiology algorithm: stratification December 17, 2020 by Jim Tol When talking about getting AI into clinical practice faster, one of the most important factors is algorithm performance. The AI software should be ... Read Post
How to build your own algorithm: cleaning the AI radiology data October 29, 2020 by Arna van Engelen The currency of the 21st century may be data instead of dollars, euros or Yens. With AI being on the rise and with all the opportunities this offers ... Read Post
Deep learning radiology: the secret of convolutional neural networks August 20, 2020 by Valerio Fortunati The application of deep learning in radiology is on the rise. Especially over the past 5 years, applying deep learning to medical imaging problems ... Read Post
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