Semiautomated segmentation of hepatocellular carcinoma tumors with MRI using convolutional neural networks.
Daniela SaidGuillermo CarbonellDaniel StockerStefanie HectorsNaik Vietti-VioliOctavia BaneXing ChinMyron SchwartzParissa TabrizianSara LewisHayit GreenspanSimon JégouJean-Baptiste SchirattiPaul JehannoBachir A TaouliPublished in: European radiology (2023)
• Semiautomated single-slice and volumetric segmentation using convolutional neural networks (CNNs) models provided fair to good performance for hepatocellular carcinoma segmentation on MRI. • CNN models' performance for HCC segmentation accuracy depends on the MRI sequence and tumor size, with the best results on diffusion-weighted imaging and T1-weighted imaging pre-contrast, and for larger lesions.