Deep Learning Combined with Radiologist’s Intervention Achieves Accurate Segmentation of Hepatocellular Carcinoma in Dual-Phase Magnetic Resonance Images

Figure 6

The heatmaps of convolutional layers at different stages of (b–d) deep convolutional neural networks (DCNNs) of an (a) input image. The ground truth (GT) of hepatocellular carcinoma (HCC) margins was presented on the patient’s hepatobiliary phase- (HBP-) magnetic resonance imaging (MRI) image. The border of the abdomen and other organs can be overserved at the shallow layer ((b) conv2_1). As the network progressed deeper, less details were kept, but the border of the abdomen was discernible ((c) conv4_1). Finally, the HCC retained a high response, while other regions were excluded ((d) deconv3_1).

(a)

(b)

(c)

(d)