@inproceedings{e6c370e0b0724d9188f9c60fbe1a4bb3,
title = "Two-stage U-Net++ for Medical Image Segmentation",
abstract = "Convolutional neural networks (CNNs) have achieved expert-level performance in many image processing applications. However, CNNs face the vanishing gradient problem when the number of layers are increased beyond a certain threshold. In this paper, a new two-stage U-Net++ (TS-UNet++) architecture is proposed to address the vanishing gradient problem. The new architecture uses two different types of deep CNNs rather than a traditional multi-stage network, the U-Net++ and U-Net architectures in the first and second stages respectively. An extra convolutional block is added before the output layer of the multi-stage network to better extract high-level features. A new concatenation-based fusion structure is incorporated in this architecture to enable deep supervision. More convolutional layers are added after each concatenation of the fusion structure to extract more representative features. The performance of the proposed method is compared with the U-Net, U-Net++ and two-stage U-Net (TS-UNet) architectures for the problem of segmenting neck muscles in a clinical MRI dataset. The architectures were evaluated using the dice similarity coefficient (DSC) and directed Hausdorff distance (DHD) measures and the results demonstrate the superior performance of the new architecture.",
keywords = "Deep Learning, MRI, Neck Muscles, Segmentation, U-Net, Whiplash",
author = "Suman, {Abdulla Al} and Shubham Sarda and Md Asikuzzaman and Webb, {Alexandra Louise} and Diana, {M. Perriman} and Murat Tahtali and {Di Ieva}, Antonio and Pickering, {Mark R.}",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2021 ; Conference date: 29-11-2021 Through 01-12-2021",
year = "2021",
doi = "10.1109/DICTA52665.2021.9647268",
language = "English",
series = "DICTA 2021 - 2021 International Conference on Digital Image Computing: Techniques and Applications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Jun Zhou and Olivier Salvado and Ferdous Sohel and Borges, {Paulo Vinicius K.} and Shilin Wang",
booktitle = "DICTA 2021 - 2021 International Conference on Digital Image Computing",
address = "United States",
}