Overview of Image Processing and Computer Vision Techniques with Medical Imaging examples
MATLAB is a popular tool used by research and development engineers developing tomographic (MRI, CT, PT), ultrasound, intravascular, endoscopic imaging, and in-vitro diagnostic devices and technologies. It's used for a variety of tasks from analyzing, enhancing, and visualizing medical images to developing advanced imaging algorithms deployed on PCs, embedded systems, and the cloud.
In this webinar, you'll learn about new image processing and computer vision capabilities relevant to the medical and healthcare industry segments.
Some of the tasks we'll explore in developing advanced predictive models include:
- New Apps in MATLAB for Medical Imaging: Introduction to apps and features to simplify image data exploration, processing, visualization, and algorithm development related to 3D images and semantic segmentation.
- Rapid Prototyping and Algorithm Development: In a full case study, learn to develop complete image processing workflows quickly and scale up easily to large datasets.
- Image Processing Algorithm Deployment: Introduction to deployment technologies that allows engineers developing algorithms in MATLAB to generate efficient code for processors, FPGAs, and GPU, to deploy them on local clusters or the cloud.
- Computer Vision Topics in Medical: Applying various advanced computer vision techniques in biomedical imaging problems for object detection, tracking, and feature extraction (for machine learning workflows).