Automatic extraction method of X-ray hand bone region of interest based on deep neural network

Abstract

An automatic extraction method of X-ray hand bone interest area based on deep neural network. For the original hand bone X-ray image, remove the black background embedded text on both sides of the image; uniformly brighten and remove the original hand bone X-ray image. Noise operation; sample and train the model M1 to obtain the hand bone X-ray image Output2 without text; normalize the size of Output2 to obtain Output3; sample and train the model M2 to intersect the hand bone, background, and hand bone background in Output3 Partially judge; based on the model M2, judge the sliding window of the image in Output3, and obtain the hand bone marker map Output4 based on the judgment value; based on Output3 and Output4, get the image Output5 with only the hand bone; optimize Output5 to get the final hand bone interest area. The invention can automatically acquire the hand bone interest area in the X-ray film.

Description

technical field [0001] The present invention relates to the fields of medical image analysis and machine learning, in particular to a method for extracting regions of interest from X-ray images of human hand bones, which belongs to the field of medical image analysis based on deep learning. Background technique [0002] Skeletal age, referred to as bone age, is determined by the degree of bone calcification in children. Bone age can more accurately reflect the developmental level of a person at each age stage from birth to full maturity. Not only that, but also in the analysis and diagnosis of endocrine diseases, developmental disorders, nutritional disorders, genetic diseases and metabolic diseases, bone age has important functions. important role. Radiologists measure a child's bone age by comparing x-rays of the child's hand to a standard for their age. The technology is stable and has been around for decades. With the improvement of parents' health awareness, the numb...

AI Technical Summary

Problems solved by technology

[0004] In order to overcome the disadvantages of low efficiency, large error and low precision of the existing X-ray hand bone region of interest extraction methods, the present invention proposes an X-ray method based on deep neural network with high efficiency, small error and high precision. The method of automatically extracting the region of interest of the hand bone in the X-ray film can not only automatically obtain the hand bone area in the X-ray film, but also automatically remove noise and adjust the brightness

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