Bridging 2D and 3D segmentation networks for computation-efficient volumetric medical image segmentation: An empirical study of 2.5D solutions

Author:

Zhang Yichi,Liao Qingcheng,Ding Le,Zhang Jicong

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference43 articles.

1. Projection-based 2.5 d u-net architecture for fast volumetric segmentation;Angermann,2019

2. Deep learning techniques for automatic mri cardiac multi-structures segmentation and diagnosis: is the problem solved?;Bernard;IEEE Trans. Med. Imaging,2018

3. Combining fully convolutional and recurrent neural networks for 3d biomedical image segmentation;Chen;Adv. Neural Inf. Process. Syst.,2016

4. A novel hybrid convolutional neural network for accurate organ segmentation in 3d head and neck ct images;Chen,2021

5. 3d u-net: learning dense volumetric segmentation from sparse annotation;Çiçek,2016

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