Research on the algorithm of organ segmentation in chest X-ray images

Medical image processing is the first step in analyzing medical images, which helps to make the images more intuitive and clearer and improve the efficiency of diagnosis. Image segmentation is an important part of image processing, and it is also a difficult point. It is a bottleneck problem that restricts the application of technologies such as 3D reconstruction. In recent years, due to the rapid development of deep learning methods, image segmentation algorithms based on deep learning have made remarkable achievements in the field of medical image segmentation. This article discusses the general algorithm framework and deep learning framework for medical image segmentation and their optimization. The final part of deep learning methodology of medical image transformation of segmentation and recognition has become complicated and abundant. The related work for medical image segmentation of X-Ray images focuses on increasing the resolution of images to raise the correct rate of images segmentation. The methods using deep learning methods for medical image processing promotes the step of the methods using traditional methods with high accuracy.