Industry News
![Image: Saliency map of deep learning model Inception V3 on the classification of Alzheimer disease. (a) A representative saliency map with anatomic overlay in 77-year-old man. (b) Average saliency map over 10 percent of Alzheimer’s Disease Neuroimaging Initiative set. (c) Average saliency map over independent test set. The closer a pixel color is to the \"High\" end of the color bar in the image, the more influence it has on the prediction of Alzheimer disease (Photo courtesy of UCSF).](https://globetechcdn.com/mobile_medicalimaging/images/stories/articles/article_images/2018-11-23/SDD-614.jpg "Image: Saliency map of deep learning model Inception V3 on the classification of Alzheimer disease. (a) A representative saliency map with anatomic overlay in 77-year-old man. (b) Average saliency map over 10 percent of Alzheimer’s Disease Neuroimaging Initiative set. (c) Average saliency map over independent test set. The closer a pixel color is to the \\"High\\" end of the color bar in the image, the more influence it has on the prediction of Alzheimer disease (Photo courtesy of UCSF)."){kind=small}
AI Predicts Alzheimer’s Disease Years before Diagnosis
A new study on the application of deep learning (DL) to detect changes in brain metabolism predictive of Alzheimer’s disease (AD) has found that artificial intelligence (AI) improves the ability of brain imaging to predict AD. More...23 Nov 2018
UK to Set Up New GBP 10 Million Centre for Medical Imaging and AI
The UK’s London Medical Imaging & Artificial Intelligence Centre for Value-Based Healthcare will train sophisticated artificial intelligence (AI) algorithms from NHS medical images and patient data, to create tools that will help clinicians speed up and improve diagnosis and care across a number of patient pathways, including dementia, heart failure and cancer. More...23 Nov 2018
New AI Algorithm Enhances Polyp Detection in Colonoscopy Procedures
Researchers at Shanghai Wision AI Co., Ltd., a developer of computer-aided diagnostic algorithms and systems to improve the accuracy and effectiveness of diagnostic imaging, have announced results of a study validating a novel machine-learning algorithm that improves detection of adenomatous polyps during colonoscopy. The AI algorithm is built on the same network architecture that is used to develop self-driving cars and is designed to enable “self-driving” in colonoscopy procedures. More...23 Nov 2018
Study Finds AI Falls Short When Analyzing Medical Data
A study conducted at the Icahn School of Medicine at Mount Sinai has found that artificial intelligence (AI) tools trained to detect pneumonia on chest X-rays suffered significant decreases in performance when tested on data from outside health systems. These findings suggest that unless AI in the medical space is carefully tested for performance across a wide range of populations, the deep learning models may not perform as accurately as expected. More...20 Nov 2018
ACR Data Science Institute Releases AI Use Cases to Accelerate AI Adoption
The American College of Radiology Data Science Institute has released a first-of-its-kind series of standardized artificial intelligence (AI) use cases that will accelerate medical imaging AI adoption. This continually updated, freely available use case series is the product of a previously missing and collaborative framework that enables efficient creation, implementation and ongoing improvement of radiological AI tools. More...12 Nov 2018
Smart POC Tele-ultrasound Devices to Boost Demand in Global Market
The global point-of-care (POC) ultrasound systems market is projected to grow at a CAGR of nearly 9% during the period 2018-2022, driven mainly by awareness programs by organizations and vendors. A key trend in the global POC ultrasound systems market is the emergence of smart POC tele-ultrasound systems, which are expected to provide a boost to the demand in the market. More...05 Nov 2018
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Clinton
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X-Ray QA Meter
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MedImaging Industry News channel updates the reader on mergers and takeovers, on cooperative agreements and on trends in the healthcare imaging industry worldwide.