Automated MRI liver segmentation for anatomical segmentation, liver volumetry, and the extraction of radiomics

ConclusionAutomated liver segmentation yields robust and generalizable segmentation performance on MRI data and can be used for volumetry and radiomic feature extraction.Clinical relevance statementLiver volumetry, anatomic localization, and extraction of quantitative imaging biomarkers require accurate segmentation, but manual segmentation is time-consuming. A deep convolutional neural network demonstrates fast and accurate segmentation performance on T1-weighted portal venous MRI.Key Points• This deep convolutional neural network yields robust and generalizable liver segmentation performance on internal, external, and public testing data.• Automated liver volumetry demonstrated excellent agreement with manual volumetry.• Automated liver segmentations can be used for robust and reproducible radiomic feature extraction.
Source: European Radiology - Category: Radiology Source Type: research