Cross Domain Deep Learning for Noise Removal from LDCT Images

Hong Xian Tsai, Li Wei Kang

研究成果: 書貢獻/報告類型會議論文篇章

2 引文 斯高帕斯(Scopus)

摘要

In this paper, an unsupervised cross domain deep learning framework for noise removal from LDCT (Low Dose Computed Tomography) images is proposed. To tackle with the problem that paired LDCT image training data for noisy images and the corresponding clean versions are rarely available in real scenarios, the presented model is trained in an unsupervised manner with unpaired training images. Relying on the auto-encoder architecture, our framework aims at learning two deep generators/decoders for producing clean and noisy images, respectively, by learning disentangling feature representations. In our generators, our deep residual blocks and the spatial and channel attention modules with dilated convolutions are used for learning multi-scale image features. To train our image generators, unsupervised adversarial domain adaption is used to learn robust and invariant image representations. For each unpaired training images, by feeding the encoded image content features from the noisy training image to the clean image generator, we aim at generating the corresponding clean image. On the other hand, by feeding the encoded features, fused by the encoded content features from the clean training image and the encoded noise features from the noisy training image, to the noisy image generator, we aim at synthesizing the noisy image. To ensure the stability of this cross domain transformation, the cycle consistency loss is also included to keep the backward transformation from the synthesized images to their respective original domains. Extensive experiments on LDCT image denoising have shown the feasibility of the proposed framework.

原文英語
主出版物標題Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
發行者Institute of Electrical and Electronics Engineers Inc.
頁面475-476
頁數2
ISBN(電子)9781665470506
DOIs
出版狀態已發佈 - 2022
事件2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 - Taipei, 臺灣
持續時間: 2022 7月 62022 7月 8

出版系列

名字Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022

會議

會議2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022
國家/地區臺灣
城市Taipei
期間2022/07/062022/07/08

ASJC Scopus subject areas

  • 人工智慧
  • 電腦科學應用
  • 硬體和架構
  • 可再生能源、永續發展與環境
  • 電氣與電子工程
  • 媒體技術
  • 健康資訊學
  • 儀器

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