EMED-UNet: An Efficient Multi-Encoder-Decoder Based UNet for Medical Image Segmentation

EMED-UNet: An Efficient Multi-Encoder-Decoder Based UNet for Medical Image Segmentation

Many current and state-of-the-art deep learning models for accurate image segmentation are based on the U-Net architecture, a convolutional neural network designed for biomedical applications. Despite its widespread adoption in the medical imaging community, U-Net has two major limitations. First, d...

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Bibliographic Details
Main Authors: Kashish D. Shah, Dhaval K. Patel, Minesh P. Thaker, Harsh A. Patel, Manob Jyoti Saikia, Bryan J. Ranger
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Deep learning
U-Net
bottleneck layer
semantic segmentation
medical image segmentation
encoder-decoder networks
Online Access:https://ieeexplore.ieee.org/document/10231330/

Internet

https://ieeexplore.ieee.org/document/10231330/

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