— Technology Description
Prof. Deshan Yang and colleagues have developed automated systems and software toolkits to provide more accurate deformable image registration (DIR) for adaptive radiotherapy and other clinical applications. In particular, they have automated tedious and labor-intensive DIR …
— Technology Description
A team of researchers at Washington University has created a machine learning method to quickly and reliably validate patient contours in digital medical images for radiation therapy and computer aided image analysis.
Currently, automated contouring tools for delineating tu…
— Background
PET-CT scanners have been widely used in the identification of tumors and localization for biopsies due to its superior ability to detect biochemical and physiological functions. However, one of the main limitations of PET-CT is the inability to visualize soft tissues, which may be impor…
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About 70 million computed tomography (CT) scans are performed in the United State alone each year. Traditional helical scanners use a single point x-ray source that rotates around the patient, acquiring images in sequential slices, which results in high quality images. But these helical scanners a…
— Technology Description
Researchers in Prof. Deshan Yang’s laboratory have developed a deep-learning method for fast, robust, automated MRI segmentation to expedite treatment planning for patients undergoing MRI-guided adaptive radiotherapy (MR-IGART). Specifically, this technology utilizes a…
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Creating...
