A segmentation network algorithm for medical images based on attention mechanism and edge predictor
Such problems as outlier and low edge segmentation accuracy easily appear in the existing convolutional neural networks for segmenting medical images.Therefore,we adopt an edge predictor module based on the attention mechanism,the variational representation of activation function,and the geodesic active contour model to develop a medical image segmentation network.Then,we design an algorithm to train the end-to-end network.The experimental results on two common datasets demonstrate that compared with other segmentation methods,the proposed method can extract more edge information and hold higher accuracy.
convolutional neural networkmedical image segmentationgeodesic active contouredge predictorattention mechanism
万方数据
维普
