Construction method and application of thoracic disease detection model
A chest disease and detection model technology, applied in the field of medical imaging, can solve problems such as difficulty in ensuring diagnostic efficiency and accuracy, and achieve the effects of improving diagnostic efficiency and accuracy, reducing diagnostic time, and improving efficiency and accuracy
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Embodiment 1
[0046] Such as figure 1 As shown, the application provides a method for constructing a chest disease detection model, including:
[0047] S101. Acquire chest X-ray images of a specified number of chest disease patients; the chest X-ray images may use a large number of existing chest X-ray images of chest disease patients.
[0048] Then in steps S102-104, image preprocessing is performed on the X-ray image to obtain preprocessed image data.
[0049] S102, performing chest X-ray image segmentation, including: using the Unet network to train a chest segmentation model, and performing chest segmentation on all chest X-ray images to obtain segmented chest X-ray images. Specifically, it includes: B11. Preliminarily locate the chest area through connected domain analysis. B12. Delete the non-image area at the edge of the chest area. Such as figure 2 As shown, the picture on the right shows that the segmented chest radiograph (chest X-ray image) can enable the Unet network to acc...
Embodiment 2
[0071] The present application also provides a chest disease detection method based on the above chest disease detection model, comprising the following steps:
[0072] A', input patient's chest X-ray image;
[0073] B', preprocessing the chest X-ray image to obtain preprocessed image data;
[0074] C'. Input the preprocessed image data into the trained chest disease detection model to detect chest diseases.
[0075] To sum up, the present application can quickly and accurately provide a chest disease detection result for the user's reference, so as to reduce the doctor's diagnosis time and improve the efficiency and accuracy of diagnosis.
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