Abstract: The present application discloses a label-free adaptive CT super-resolution reconstruction method, device and system based on a generative network, which comprises the following modules: an acquisition module configured for acquiring low-resolution original CT image data; a preprocessing module configured for performing super-resolution reconstruction on original CT images based on total variation to obtain an initial value; and a super-resolution reconstruction module configured for performing high-resolution reconstruction on the initial value. According to the present application, a parameter fine-tuning method is adopted, and a CT reconstruction network which is not suitable for a certain patient is adjusted into a network which is suitable for the patient's situation on the premise of not using a large number of data sets for training; only the low-resolution CT data of the patient is used in this process, and the corresponding high-resolution CT data is not needed as a label.

Abstract: Disclosed is an image denoising method and apparatus based on wavelet high-frequency channel synthesis. Image data are expanded to a plurality of frequency-domain channels, a plurality of “less-noise” channels and a plurality of “more-noise” channels are grouped through a noise-sort algorithm, and a denoising submodule and a synthesis submodule based on style transfer are combined to form a generative network. A discriminative network is established to add a constraint to the global loss function. After iteratively training the GAN model described above, the denoised image data can be obtained through wavelet inverse transformation. The disclosed algorithm can effectively solve the problem of “blurring” and “loss of details” introduced by traditional filtering or CNN-based deep learning methods, which is especially suitable for noise-overwhelmed image data or high dimensional image data.

Abstract: Bifidobacterium breve CCFM1025, foods fermented thereby and an application thereof in the preparation of an anti-depression drug, an anti-inflammatory bowel disease drug, an anti-obesity drug, health products and functional foods.

Abstract: Bifidobacterium longum subsp. infantis CCFM687, a fermented food thereof, and an application of the same in preparing a drug, health care product, or food against depression, autism, inflammatory bowel disease, obesity, or type 1 diabetes.

Abstract: The disclosure discloses P. acidilactici CCFM6432 for alleviating depression, food fermented thereby and application thereof. The P. acidilactici CCFM6432 of the disclosure can be used to prepare food, health-care products and drugs with the functions of resisting depression, resisting inflammation, resisting inflammatory bowel disease, resisting obesity and resisting type I diabetes. The disclosure further provides fermented food. The fermented food is produced by fermentation using the P. acidilactici CCFM6432, and the fermented food includes solid food, liquid food, and semi-solid food. The P. acidilactici CCFM6432 has very broad application prospects.