Nested block self-attention multiple resolution residual network for multiorgan segmentation from CT.

ABSTRACT:

Background

Fast and accurate multiorgans segmentation from computed tomography (CT) scans is essential for radiation treatment planning. Self-attention(SA)-based deep learning methodologies provide higher accuracies than standard methods but require memory and computationally intensive calculations, which restricts their use to relatively shallow networks.

Purpose

Our goal was to develop and test a new computationally fast and memory-efficient bidirectional SA method called nested block self-attention (NBSA), which is applicable to shallow and deep multiorgan segmentation networks.

Methods

A new multiorgan segmentation method combining a deep multiple resolution residual network with computationally efficient SA called nested block SA (MRRN-NBSA) was developed and eva

SUBMITTER: Jiang J 

PROVIDER: S-EPMC9908007 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature