Medical image processing method based on dictionary studying upsampling

Abstract

The invention discloses a medical image processing method based on dictionary studying upsampling, and belongs to the technical field of image processing. The medical image processing method is realized by the following steps of: inputting an original medical image; cutting and reinforcing the original medical image; extracting the characteristics of the cut and reinforced medical image to obtain a training sample set and a testing sample set according the extracted characteristics; finding out boundary points of weakness samples from the training sample set to obtain the number of new samples to be generated according to the situation of the neighborhoods of the boundary points; generating required new samples by utilizing a sparse ligature and point getting method; adding the new samples into the training sample set to form a new training sample set; carrying out classifying diagnosis to the new training sample set to get a classifier; and diagnosing the testing sample set by adopting the classifier to get a final diagnosis result. The medical image processing method has the advantages of high recognition rate and strong generalization capability on medical image diagnosis, and can be used for medical workers to evaluate disease prognosis and therapeutic effect.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to medical image processing, which can be used for monitoring disease distribution, researching pathogenesis and assisting disease diagnosis. Background technique [0002] The rapid development of computer science and technology has had a huge impact on the medical field. People are trying to let computers gradually replace humans to achieve challenging tasks such as automatic diagnosis of diseases. Medical images play an important role in clinical diagnosis. Since Rontgen discovered X-rays in 1895, especially in 1979, CT technology appeared, which greatly promoted the development of imaging medicine. In the past thirty years, new imaging techniques have emerged in an endless stream. [0003] However, due to the high value required by the source and the issue of personal privacy, there are fewer medical images with lesions than normal images, which causes data imbalance an...

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Problems solved by technology

[0006] The purpose of the present invention is to overcome the deficiencies of the above-mentioned prior art. Aiming at problems such as unbalanced medical image data, low diagnostic recognition rate and weak generalization ability, a medical image processing method based on dictionary learning and upsampling is proposed to improve medical image quality. Imaging diagnostic recognition rate and enhanced generalization ability

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