Meidcal Image Training Lab
Introduction
Artificial intelligence technology has achieved many breakthroughs in medical image processing, mainly including intelligent identification, automatic segmentation, three-dimensional reconstruction and quantification of lesions in CT, MRI and ultrasound images, as well as intelligent diagnosis and prognosis assessment of diseases in the later stage. This training lab covers the typical applications of artificial intelligence in medical image processing such as CT, MRI and ultrasound images, and provides detailed medical image processing and deep learning model training process, including data labeling, model training, model call and deployment, to help students quickly get started and master relevant knowledge and skills.
Applicable Majors: Medical Information Engineering/Intelligent Medical Engineering/Medical Imaging Technology/Computer related majors
Course Products: CT Imaging Principle Training, Ultrasonic Imaging Principle Training, Medical Image Enhancement Training, Image Segmentation Training, Image Registration Training, CT Simulation Operation Training
Project Products: head CT image motion artifact recognition, left ventricle automatic segmentation of echocardiography, head CT image motion artifact recognition based on neural network architecture search (NAS), brain CT simulation image generation based on DCGAN, automatic segmentation of COVID-19 CT image based on AI, brain tumor MRI image segmentation based on nnU-Net
Application Scenarios: professional teaching, comprehensive practical training, competition training
• Using cutting-edge algorithms of artificial intelligence to solve hot issues in medical imaging
The project technology covers all
• The project covers the whole technology chain of medical image processing, namely the core technology fields of imaging, enhancement, segmentation and registration
Self-developed imaging algorithm
• The CT imaging process in the simulation system can be seen intuitively
Artificial intelligence technology has achieved many breakthroughs in medical image processing, mainly including intelligent identification, automatic segmentation, three-dimensional reconstruction and quantification of lesions in CT, MRI and ultrasound images, as well as intelligent diagnosis and prognosis assessment of diseases in the later stage. This training lab covers the typical applications of artificial intelligence in medical image processing such as CT, MRI and ultrasound images, and provides detailed medical image processing and deep learning model training process, including data labeling, model training, model call and deployment, to help students quickly get started and master relevant knowledge and skills.
Applicable Majors: Medical Information Engineering/Intelligent Medical Engineering/Medical Imaging Technology/Computer related majors
Course Products: CT Imaging Principle Training, Ultrasonic Imaging Principle Training, Medical Image Enhancement Training, Image Segmentation Training, Image Registration Training, CT Simulation Operation Training
Project Products: head CT image motion artifact recognition, left ventricle automatic segmentation of echocardiography, head CT image motion artifact recognition based on neural network architecture search (NAS), brain CT simulation image generation based on DCGAN, automatic segmentation of COVID-19 CT image based on AI, brain tumor MRI image segmentation based on nnU-Net
Application Scenarios: professional teaching, comprehensive practical training, competition training
Feature
Project cutting edge• Using cutting-edge algorithms of artificial intelligence to solve hot issues in medical imaging
The project technology covers all
• The project covers the whole technology chain of medical image processing, namely the core technology fields of imaging, enhancement, segmentation and registration
Self-developed imaging algorithm
• The CT imaging process in the simulation system can be seen intuitively
