Pancreas Segmentation via Spatial Context based U-net and Bidirectional LSTM

03/03/2019
by   Hao Li, et al.
4

Pancreas is characterized by small size and irregular shape, so achieving accurate pancreas segmentation is challenging. Traditional 2D pancreas segmentation network based on the independent 2D image slices, which often leads to spatial discontinuity problem. Therefore, how to utility spatial context information is the key point to improve the segmentation quality. In this paper, we proposed a divide-and-conquer strategy, divided the abdominal CT scans into several isometric blocks. And we designed a multiple channels convolutional neural network to learn the local spatial context characteristics from blocks called SCU-Net. SCU-Net is a partial 3D segmentation idea, which transforms overall pancreas segmentation into a combination of multiple local segmentation results. In order to improve the segmentation accuracy for each layer, we also proposed a new loss function for inter-slice constrain and regularization. Thereafter, we introduced the BiCLSTM network for stimulating the interaction between bidirectional segmentation sequence, thus making up the boundary defect and fault problem of the segmentation results. We trained SCU-Net+BiLSTM network respectively, and evaluated segmentation result on the NIH data set. Keywords: Pancreas Segmentation, Convolutional Neural Networks, Recurrent Neural Networks, Deep Learning, Inter-slice Regularization

READ FULL TEXT

page 2

page 4

page 5

research
07/16/2017

Improving Deep Pancreas Segmentation in CT and MRI Images via Recurrent Neural Contextual Learning and Direct Loss Function

Deep neural networks have demonstrated very promising performance on acc...
research
03/13/2020

Recurrent convolutional neural networks for mandible segmentation from computed tomography

Recently, accurate mandible segmentation in CT scans based on deep learn...
research
10/09/2018

Comparison of U-net-based Convolutional Neural Networks for Liver Segmentation in CT

Various approaches for liver segmentation in CT have been proposed: Besi...
research
07/19/2018

ISIC 2018-A Method for Lesion Segmentation

Our team participate in the challenge of Task 1: Lesion Boundary Segment...
research
09/05/2016

Combining Fully Convolutional and Recurrent Neural Networks for 3D Biomedical Image Segmentation

Segmentation of 3D images is a fundamental problem in biomedical image a...
research
03/30/2018

Pancreas Segmentation in CT and MRI Images via Domain Specific Network Designing and Recurrent Neural Contextual Learning

Automatic pancreas segmentation in radiology images, eg., computed tomog...
research
03/25/2018

P2P-NET: Bidirectional Point Displacement Net for Shape Transform

We introduce P2P-NET, a general-purpose deep neural network which learns...

Please sign up or login with your details

Forgot password? Click here to reset