Lesion classification method and device, and training method of focus classification model

Abstract

The invention provides a lesion classification method and device, and a training method of a lesion classification model. The lesion classification method comprises the steps that a first lesion areain a first medical image and a second lesion area in a second medical image are acquired, wherein the first medical image and the second medical image are images obtained by shooting an examination part of the same examination object at different angles, and the first lesion area and the second lesion area are image areas corresponding to the same lesion in the first medical image and the second medical image respectively; feature extraction is respectively performed on the first lesion area and the second lesion area; the features of the first lesion area and the features of the second lesionarea are fused to obtain a first fused feature of the lesion; and according to the first fusion feature, the lesions are classified. Therefore, the resolution capability of the lesion types can be improved, and the lesion classification accuracy is improved.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to a lesion classification method and device, and a training method for a lesion classification model. Background technique [0002] In recent years, with the rapid development of computer science technology and medical imaging engineering, many advanced medical imaging devices have appeared in the world, providing medical images of various modalities for clinical medical diagnosis. These medical images can reflect the structure of the human body, Information about organs and diseased tissues. [0003] However, in the prior art, the lesion type is usually identified by the doctor observing the characteristics of the lesion in the medical image, and the identification result is closely related to the doctor's clinical experience, especially for the situation where the lesion type is difficult to identify, the identification is difficult , for example, it is difficul...

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Problems solved by technology

[0003] However, in the prior art, the lesion type is usually identified by the doctor observing the characteristics of the lesion in the medical image, and the identification result is closely related to the doctor's clinical experience, especially for the situation where the lesion type is difficult to identify, the identification is difficult , for example, it is difficult to tell whether a thoracolumbar compression fracture is old or fresh in digital radiography (DR) images

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