The integration of artificial intelligence (AI) into medicine has by far been the hottest topic at nearly all medical conferences for radiology, cardiology and several other subspecialties over the past two...
Radiomics
Radiomics is the study of information hidden in imaging exams that machine algorithms are trained to identify to help doctors more accurately diagnose patients, stage cancers, determine optimum therapies, predict patient outcomes or their risk level choose the radiation therapy dose level of risk. The field of medical study extracts large amounts of quantitative features from medical images using data characterization algorithms. These features, called radiomic features, may be able to uncover disease characteristics that fail to be appreciated by the naked eye. It is expected this field will be dominated by artificial intelligence software in the coming years.
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A novel technique that uses mammography to determine the biological tissue composition of a tumor could help reduce unnecessary breast biopsies, according to a new study appearing in the journal Radiology
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Genomics can be used to assess a patient's radiosensitivity, which can be used to increase or decrease the radiation that needs to be delivered to treat the tumor and spare surrounding healthy tissue. ...
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A discussion with Martin Vallieres, Ph.D., post-doctoral fellow at McGill University, Montreal, Canada. He spoke on this topic in sessions at the American Association of Physicists in Medicine (AAPM) 2018 meeting.
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Information from brain magnetic resonance images (MRIs) can help identify people with attention deficit hyperactivity disorder (ADHD) and distinguish among subtypes of the condition, according to a study appearing online in the journal Radiology.
Videos | Radiation Oncology | November 06, 2018
Genomics can be used to assess a patient's radiosensitivity, which can be used to increase or decrease the radiation...
Cherenkov radiation imaging during radiation therapy
Blog | AAPM | August 14, 2018
I attended the American Association of Physicists in Medicine (AAPM)...
Videos | Radiomics | August 09, 2018
A discussion with Martin Vallieres, Ph.D., post-doctoral fellow at McGill University, Montreal, Canada. He spoke on...
News | PACS | May 30, 2018
May 30, 2018 — U.S.-based Softek Illuminate and the entrepreneurial French firm Medexprim will be combining,...
News | Advanced Visualization | May 29, 2018
May 29, 2018 — A team of researchers including investigators from Mayo Clinic has identified a technology to address...
MRI scans of patients with radiation necrosis (above) and cancer recurrence (below) are shown in the left column. Close-ups in the center column show the regions are indistinguishable on routine scans. Radiomic descriptors unearth subtle differences showing radiation necrosis, in the upper right panel, has less heterogeneity, shown in blue, compared to cancer recurrence, in the lower right, which has a much higher degree of heterogeneity, shown in red. Credit: Pallavi Tiwari
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October 25, 2016 — Computer programs have defeated humans in Jeopardy!, chess and Go. Now a program developed at Case...
News | July 30, 2014
July 30, 2014 — Information hidden in imaging tests could help doctors more accurately choose the...