Figure 1 | Scientific Reports

Figure 1

From: Canal-Net for automatic and robust 3D segmentation of mandibular canals in CBCT images using a continuity-aware contextual network

Figure 1

The Canal-Net architecture with a 3D encoder-decoder under a multi-task learning framework consisting of time-distributed convolution blocks, multi-scale inputs, skip connection, and bidirectional convolutional LSTM (ConvLSTM) with side-output layers. The bidirectional ConvLSTM was utilized to capture anatomical context information, and a multi-task learning approach was performed to learn overall MC volume and structural continuity.

Back to article page