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New material shows promise for MRI
Scientists from Marconi Medical Systems and the Imperial College of London have developed a magnetic material that promises to improve MRI performance. The new material concentrates and shapes radio-frequency flux patterns used in data acquisition and is
Scientists from Marconi Medical Systems and the Imperial College of London have developed a magnetic material that promises to improve MRI performance. The new material concentrates and shapes radio-frequency flux patterns used in data acquisition and is less vulnerable than current materials to external interference. The capability of the substance as a flux guide has been used to remotely image a human finger.
The material was developed as part of a collaboration among the physics department of Imperial College, the Clinical Sciences Centre MR Unit of the Imperial Medical School, and Marconi Caswell in the U.K. The work led to the discovery of a new class of microstructured materials, which is part of a larger family called photonic band gap materials. The microstructured material now being developed by Marconi is designed specifically for use in MRI. It has a high magnetic permeability for RF fields but not for static fields. It also has applications as a magnetic screen and potentially as a magnetic lens.
FDA Approves Fluorescence Imaging System for Detecting Residual Breast Cancer
April 18th 2024The combination of the optical imaging agent Lumisight and the fluorescence imaging device Lumicell Direct Visualization System, collectively known as LumiSystem, reportedly offers 84 percent accuracy with real-time detection of residual breast cancer after lumpectomy procedures.
Study of Ofatumumab for Multiple Sclerosis Shows 'Profoundly Suppressed MRI Lesion Activity'
April 17th 2024The use of continuous ofatumumab in patients within three years of a relapsing multiple sclerosis diagnosis led to substantial reductions in associated lesions on brain MRI scans, according to research recently presented at the American Academy of Neurology (AAN) conference.
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
April 15th 2024Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.
