Mammary gland molybdenum target image segmentation device, electronic equipment, medical equipment and medium
A technology for electronic equipment and mammary glands, which is applied in image analysis, image enhancement, image data processing, etc., and can solve problems such as reducing accuracy and reducing segmentation efficiency.
Pending Publication Date: 2021-09-14
神州医疗科技股份有限公司
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However, the methods in related technologies have certain limitations. Only segmenting the pectoralis major region will lead to a decrease in the accuracy rate in the calculation of gland classification and lesion detection. Secondly, the mammography image segmentation method based on deep learning is still Need more process of adjusting parameters, which reduces the efficiency of segmentation
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[0045] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only It is a part of the embodiments of this application, but not all of them. The components of the embodiments of the application generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of the embodiments of the application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art wi...
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The embodiment of the invention provides a mammary gland molybdenum target image segmentation device, electronic equipment, medical equipment and a medium. The electronic equipment comprises a memory and a processor, wherein the memory is configured to store a computer program, and the processor executes the program to realize the following mammary gland molybdenum target image segmentation method: acquiring a mammary gland molybdenum target image; determining a target segmentation line according to an average value of non-zero pixels on the mammary gland molybdenum target image; acquiring a mammary gland area from the mammary gland molybdenum target image according to the target segmentation line; performing data analysis based on the mammary gland area, so the mammary gland area can be efficiently and accurately acquired from the mammary gland molybdenum target image, noise interference (such as noise interference brought by a pectoralis major area in the nidus detection process) in the nidus detection process is reduced, and the accuracy of subsequent data analysis is improved.
Description
technical field [0001] The embodiments of the present application relate to the field of image segmentation, and in particular to a mammography image segmentation device, electronic equipment, medical equipment and media. Background technique [0002] In the related art, regarding the segmentation of mammography images, traditional machine learning is usually used to segment the nipple region and the pectoralis major region. However, the methods in related technologies have certain limitations. Only segmenting the pectoralis major region will lead to a decrease in the accuracy rate in the calculation of gland classification and lesion detection. Secondly, the mammography image segmentation method based on deep learning is still It requires more process of adjusting parameters, which reduces the segmentation efficiency. [0003] Therefore, how to eliminate the noise interference of the non-breast region on the lesion detection of the breast region and improve the accuracy of...
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Login to View More IPC IPC(8): G06T7/11G06N3/04G06N3/08
CPCG06T7/11G06N3/04G06N3/08G06T2207/20081G06T2207/20084G06T2207/30068G06T2207/30096
Inventor 史文钊许娟陈灿灿
Owner 神州医疗科技股份有限公司