A detection device based on fusion classification of lung medical images

Abstract

The invention claims a detection device based on fusion classification of lung medical images, the device comprising: an obtaining section obtaining a lung CT scan image of the patient; a preprocessing unit that performs preprocessing to obtain a binary gray-scale image; a morphological etching and expansion part, which performs morphological etching operation to obtain an etched image, and performs expansion operation on the binary gray image to obtain an expanded image; an arithmetic unit that performs an on-off operation on the etched image to obtain an on-off arithmetic diagram, and performs a closed operation on the expanded image to obtain a closed arithmetic diagram; a Fourier transform unit, which obtains a Fourier transform value; a lung medical image fusion classification module,which is used for fusion classification and discrimination of lung CT scanned images; and a focus detection unit configured to determine a suspected lesion area of the patient by combining the Fourier transform value with a fusion classification discrimination result. The detection device can reduce the complexity and improve the identification and diagnosis accuracy of lung focus.

Description

technical field [0001] The invention belongs to the technical field of medical image processing, in particular to a detection device based on fusion and classification of lung medical images. Background technique [0002] The existing lung medical image fusion technology is mainly for two different modal medical images. According to the different medical image modalities, the medical image fusion system can be divided into three types: anatomical medical image and anatomical medical image fusion, anatomical medical image Fusion with functional medical images and fusion of functional medical images with functional medical images. The MRI-PET and MRI-SPECT medical image fusion system belongs to the fusion of anatomical medical images and functional medical images. The input images of this system are grayscale and pseudo-color. The MRI-PET combination kit launched by Philips combines a commercial MRI imaging scanner with a PET with special shielding. The images obtained have i...

AI Technical Summary

Problems solved by technology

In terms of image decomposition and reconstruction methods, image fusion methods based on the frequency domain use Fourier transform and inverse Fourier transform to decompose and reconstruct image signals at different scales, but this type of method has high time complexity and runs The characteristics of long time, which contradicts the high real-time medical aided diagnosis, and has very high requirements on the hardware and software facilities of the experimental platform.

Later, researchers proposed to use spatial domain filters to process images to perform multi-scale decomposition and reconstruction of input images. Although this type of method can quickly perform image decomposition and reconstruction, the image fusion method based on spatial domain has poor noise immunity.

However, the existing methods use the same feature for fusion of medical images of different modalities.

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