[Open Source Project] Medical image analysis and diagnosis open source project based on image recognition

Author: Zen and the Art of Computer Programming

1.1 What is medical imaging?

Medical imaging is a non-invasive biological image of medical organs inside or outside the body. It can be a complete X-ray slice, a CT scan, or an MRI or PET scan, or even a live tracking image seen through X-ray and electron microscopy. Medical imaging has important application value in clinical diagnosis, image processing, nuclear medicine treatment and other aspects.

1.2 Traditional medical image analysis methods

Traditional medical image analysis methods can be divided into two categories: computer-assisted treatment and manual reading. Computer-assisted therapy is a process in which programs are written to automatically identify and treat abnormal changes in the patient's hand or brain epidermal areas. For example, patients with heart disease will undergo multiple echocardiograms (i.e., large CT scans) under bilateral medical orders, and then machine learning or deep learning algorithms will automatically detect symptoms such as cardiac bleeding, excessive pressure, or hypoxia. Another area is manual reading, where a doctor or nurse manually marks areas of concern from a patient's X-ray or CT scan. How this manual inspection is done varies from hospital to hospital.

In addition to the above two methods, there are some other fields that also use medical imaging technology. For example, cerebral hemorrhage and tumor resection are two application cases of medical imaging technology in psychiatric diagnosis and treatment. Currently, clinical trials of novel coronavirus (COVID-19) are ongoing in many countries and regions around the world. Many hospitals are already exploring the use of medical imaging to support clinical processes and provide better diagnostic information.

1.3 Medical image analysis method based on image recognition

With the rapid development of digital technology, medical image analysis methods based on image recognition have been increasingly widely used. This type of method uses computer vision, pattern recognition, machine learning and other technologies to extract useful information and help doctors and scientific researchers quickly and accurately diagnose and manage various diseases. Currently, there are many excellent open source projects that use machine learning technology to solve medical imaging problems. For example, AlphaStar proposed by DeepMind is a powerful adversarial agent

Guess you like

Origin blog.csdn.net/universsky2015/article/details/131861827