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GTC Silicon Valley-2019 ID:S9272:A Deep Learning-Based Method for Automated Volumetric Assessment of Liver Lesions

Daniel Golden(Arterys)
Radiological assessment and quantification of liver lesions currently relies on measurements of longest linear diameter to quantify size, which is a misleading way to measure irregularly shaped lesions. Volumetric assessment, on the other hand, gives a much better impression of overall lesion size. One of the greatest roadblocks to calculating lesion volume is the amount of time it takes to demarcate the boundaries of an individual lesion. Arterys is working on empowering the radiologist with an automated method for volumetric assessment of liver lesions. This automated method is built using a convolutional network. When integrated into Arterys web platform, it enables volumetric assessment with a single mouse click.