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AI and personalized medicine to raise the bar in radiology reporting New innovations could provide myriad benefits to clinical workflow

Canon adds radiation oncology functioning to Aquilion CTs Can be shared between radiology and radiation oncology departments

Siemens focuses on digitalization at HIMSS Its expanded digital service portfolio will be on display

Fujifilm to unveil latest version of Synapse 3D platform at HIMSS Five new capabilities for advanced visualization

Philips and MIM Software collab to streamline radiotherapy treatment planning Integrate portfolios of CT, MR and software solutions

Canon Medical debuts Aqilion Start CT system at Arab Health Designed for areas that lack access to diagnostic CT scanners

Dennis Durmis MITA names chair of board of directors

Centerline Biomedical submits IOPS system for FDA clearance Designed as alternative to X-ray fluoroscopy

Paper challenges 'legacy' use of lead apron patient shielding Divergent views from medical physicists, technologists

Philips unveils Azurion angiography system with FlexArm positioning System moves on eight different axes with single controller

Zebra Medical Vision unveils deep learning research for automated chest X-ray

by John R. Fischer , Staff Reporter

The unveiling of the Israeli enterprise’s research follows the recent CE markings for its seventh AI imaging algorithm, designed to detect suspected malignant lesions in mammograms, and its bleed detection algorithm.

In addition to the unveiling of its research, Zebra Medical Vision also announced its C round funding of $30 million, bring its total investment as a company to $50 million. AMoon Ventures led the investment, which included Aurum, Johnson & Johnson Innovation JJDC Inc., Intermountain Healthcare, and leading global AI scientists, professor Fei Fei Lee and Richard Socher.
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The company is currently exploring a similar technique for AP chest X-ray scans, and musculoskeletal and abdominal radiographies.

The findings are available on the arXiv.org e-Print archive and will be presented at the 21st International Conference on Medical Image Computing and Computer Assisted Intervention this September in Granada, Spain.

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