Introduction
Artificial intelligence has made significant breakthroughs in medical image processing, including the intelligent recognition, automatic segmentation, three-dimensional reconstruction, and quantification of lesions in CT, MRI, and ultrasound images, as well as the subsequent intelligent diagnosis and prognosis assessment. This laboratory covers the typical applications of artificial intelligence in medical imaging, including CT, MRI, and ultrasound images, and provides detailed processes of medical image processing and deep learning model training, including data annotation, model training, model call and deployment, to help students quickly get started and master relevant knowledge and skills.
Corporate Positions: Data Collection and Annotation Engineer, AI Training Engineer, AI Application Development Engineer
Applicable Majors: AI Engineering Technology/Medical Imaging Technology/Computer-related majors
Course Products: professional core courses and professional extension courses on imaging, image segmentation, image enhancement and other medical aspects
Project Products: a number of practical training projects centering on image segmentation, artifact recognition, image simulation and other technologies based on the background of medical imaging industry
Application scenarios: Professional teaching,
comprehensive training, competition training
Feature
State-of-the-art and focused
Utilizing cutting-edge artificial
intelligence algorithms to solve hot issues in medical imaging
Technology coverage across the board
The project covers the entire technology
chain of medical imaging processing, including core technology areas such as
imaging, enhancement, segmentation, and registration.
Self-developed imaging algorithm
The CT imaging process in the simulation
system is visually visible