MDA-Net: Multi-Dimensional Attention-Based Neural Network for 3D Image Segmentation

• URL: http://arxiv.org/abs/2105.04508v1
• Date: Mon, 10 May 2021 16:58:34 GMT
• Title: MDA-Net: Multi-Dimensional Attention-Based Neural Network for 3D Image Segmentation
• Authors: Rutu Gandhi and Yi Hong
• Abstract summary: We propose a multi-dimensional attention network (MDA-Net) to efficiently integrate slice-wise, spatial, and channel-wise attention into a U-Net based network. We evaluate our model on the MICCAI iSeg and IBSR datasets, and the experimental results demonstrate consistent improvements over existing methods.
• Score: 4.221871357181261
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Segmenting an entire 3D image often has high computational complexity and requires large memory consumption; by contrast, performing volumetric segmentation in a slice-by-slice manner is efficient but does not fully leverage the 3D data. To address this challenge, we propose a multi-dimensional attention network (MDA-Net) to efficiently integrate slice-wise, spatial, and channel-wise attention into a U-Net based network, which results in high segmentation accuracy with a low computational cost. We evaluate our model on the MICCAI iSeg and IBSR datasets, and the experimental results demonstrate consistent improvements over existing methods.

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