Fully automated deep learning based auto-contouring of liver segments and spleen on contrast-enhanced CT images
Aashish C. Gupta,
Guillaume Cazoulat,
Mais Al Taie
et al.
Abstract:Manual delineation of liver segments on computed tomography (CT) images for primary/secondary liver cancer (LC) patients is time-intensive and prone to inter/intra-observer variability. Therefore, we developed a deep-learning-based model to auto-contour liver segments and spleen on contrast-enhanced CT (CECT) images. We trained two models using 3d patch-based attention U-Net ($${{\text{M}}}_{{\text{paU}}-{\text{Net}}})$$
M
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