Medical photographing data acquiring method and medical photographing imaging system

Abstract

The invention belongs to the field of medical photographing technology, and discloses a medical photographing data acquiring method and a medical photographing imaging system. The medical photographing imaging system comprises an image acquisition module, a master control module, an image enhancement module, an image identification module, a characteristic extracting module, an image classification module, an analysis module, a data storage module and a display module. According to the method, through the imaging identification module, a trained deep neural network model has a symptom pictureautomatic identification function; the symptom picture is input into the deep neural network module, and the area with possible malignant lesion in the symptom picture can be identified, thereby realizing benign-malignant classification of the symptom picture, and saving time and labor in the whole process. Through the image classification module, probability distribution of the tissue lesion image is described by means of an expert system. The medical photographing data acquiring method can be used as a universal characteristic expression method and has high applicability for different imagekinds. Furthermore the medical photographing data acquiring method has relatively high classification performance in a relatively short characteristic length.

Description

technical field [0001] The invention belongs to the technical field of medical imaging, and in particular relates to a method for acquiring medical photographic data and a medical photographic imaging system. Background technique [0002] Medical photography refers to the technology and processing process of obtaining internal tissue images of the human body or a certain part of the human body in a non-invasive manner for medical treatment or medical research. It includes the following two relatively independent research directions: medical imaging system and medical image processing. The former refers to the process of image formation, including the research on imaging mechanism, imaging equipment, imaging system analysis and other issues; the latter refers to the further processing of the obtained image, the purpose of which is to restore the original image that is not clear enough, or It is to highlight certain feature information in the image, or to classify the image a...

AI Technical Summary

Problems solved by technology

[0004] The existing medical imaging image recognition process is not only time-consuming and labor-intensive, but also relies on experience, and the accuracy rate is not ideal, and doctors with different experience may have different recognition conclusions for the same disease picture;

[0005] At the same time, some existing feature extraction methods for tissue disease images are to extract manually designed features. Due to the diversity and complexity of disease images, these manually designed features cannot accurately distinguish the categories of disease images.

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