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

Rutu Gandhi; Yi Hong

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arXiv · 2105.04508

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

Rutu Gandhi·Yi Hong

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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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BibTeX RIS

Rutu Gandhi, Yi Hong. 2021-05-10. MDA-Net: Multi-Dimensional Attention-Based Neural Network for 3D Image Segmentation. https://arxiv.org/abs/2105.04508

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