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  • Open Access

    ARTICLE

    A Novel Unsupervised MRI Synthetic CT Image Generation Framework with Registration Network

    Liwei Deng1, Henan Sun1, Jing Wang2, Sijuan Huang3, Xin Yang3,*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2271-2287, 2023, DOI:10.32604/cmc.2023.039062 - 29 November 2023

    Abstract In recent years, radiotherapy based only on Magnetic Resonance (MR) images has become a hot spot for radiotherapy planning research in the current medical field. However, functional computed tomography (CT) is still needed for dose calculation in the clinic. Recent deep-learning approaches to synthesized CT images from MR images have raised much research interest, making radiotherapy based only on MR images possible. In this paper, we proposed a novel unsupervised image synthesis framework with registration networks. This paper aims to enforce the constraints between the reconstructed image and the input image by registering the reconstructed… More >

  • Open Access

    ARTICLE

    Tight Sandstone Image Augmentation for Image Identification Using Deep Learning

    Dongsheng Li, Chunsheng Li*, Kejia Zhang, Tao Liu, Fang Liu, Jingsong Yin, Mingyue Liao

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 1209-1231, 2023, DOI:10.32604/csse.2023.034395 - 26 May 2023

    Abstract Intelligent identification of sandstone slice images using deep learning technology is the development trend of mineral identification, and accurate mineral particle segmentation is the most critical step for intelligent identification. A typical identification model requires many training samples to learn as many distinguishable features as possible. However, limited by the difficulty of data acquisition, the high cost of labeling, and privacy protection, this has led to a sparse sample number and cannot meet the training requirements of deep learning image identification models. In order to increase the number of samples and improve the training effect… More >

  • Open Access

    REVIEW

    A Survey of GAN Based Image Synthesis

    Jiahe Ni*

    Journal of Information Hiding and Privacy Protection, Vol.4, No.2, pp. 79-88, 2022, DOI:10.32604/jihpp.2022.039751 - 17 April 2023

    Abstract Image generation is a hot topic in the academic recently, and has been applied to AI drawing, which can bring Vivid AI paintings without labor costs. In image generation, we represent the image as a random vector, assuming that the images of the natural scene obey an unknown distribution, we hope to estimate its distribution through some observation samples. Especially, with the development of GAN (Generative Adversarial Network), The generator and discriminator improve the model capability through adversarial, the quality of the generated image is also increasing. The image quality generated by the existing GAN More >

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