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Medical Image Processing

Offered By: MathWorks via Coursera

Tags

Deep Learning Courses MATLAB Courses Image Segmentation Courses Image Analysis Courses Medical Imaging Courses MRI Courses

Course Description

Overview

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Medical image processing is pivotal in diagnosing diseases, planning treatment, and monitoring patients. Recent advances are revolutionizing how healthcare professionals understand and interact with complex medical conditions. This course is designed to equip engineers, scientists, and healthcare professionals with the in-demand skills to work with raw medical image data, enabling advancements in patient care and contributing to groundbreaking research in medical diagnostics and treatment strategies. Throughout this course, you will learn how to import and analyze common medical image formats, accurately view 2D and 3D images, and adjust image orientation and contrast for better analysis. The course takes you deeper into aligning and labeling 3D images like MRIs, equipping you with essential skills for segmentation and deep learning applications. By the end, you'll be proficient in identifying critical regions within medical images and extracting those regions for further analysis. In this course, you will use MATLAB, the go-to choice for millions working in engineering and science. MATLAB is an intuitive, low-code environment. You will use the specialized Medical Imaging Toolbox to simplify importing and visualizing complicated medical data files so you can quickly accomplish your image processing tasks. To be successful in this course, you should have some prior exposure to MATLAB. To familiarize yourself with MATLAB, complete the free, two-hour MATLAB Onramp. If you want more in-depth image processing skills, you can also enroll in the Image Processing for Engineering and Science specialization. The skills learned in the specialization can be applied to medical images.

Syllabus

  • Working with Medical Images
  • Working with Medical Volumes
  • Labeling Medical Images

Taught by

Brandon Armstrong and Cris LaPierre

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