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Michael DAndrea,
Ivan Tarapov,
Mazen Zawaideh,
Nikhil Bikhchandani,
and
Emily Lindemer
Register for this course and see more details by visiting:
OpenCourser.com/course/v8lzhg/applying
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What's inside
Syllabus
In this lesson, we will introduce the course and instructors. We will give you an overview of the context for AI in 3D medical imaging space, and cover the objectives of the course.
Read more
Syllabus
In this lesson, we will introduce the course and instructors. We will give you an overview of the context for AI in 3D medical imaging space, and cover the objectives of the course.
Read more
In this lesson, we cover the basic terminology and concepts related to 3D medical imaging. We will look at the problem space from a clinical standpoint and learn how CT and MR scanners produce images.
In this lesson, we will dive deeper into medical imaging formats NIFTI and DICOM, how scanner data is represented, and how to read medical volumes stored in these files and analyze them.
In this lesson, we cover the basics of building deep neural networks for 3D medical imaging (mostly segmentation & classification) and performance evaluation from a software and clinical perspective.
In this lesson, we'll talk about clinical networks, architecture, and AI deployment, tools and their use by data scientists and clinicians, as well as medical device regulation and data privacy.
In this project, you will curate a dataset of brain MRIs, train a segmentation on a CNN, and integrate this into a clinical network to quantify hippocampal volume for Alzheimer's progression.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces core terminology of 3D medical imaging
Builds a solid foundation for beginners in 3D medical imaging
Teaches skills and knowledge that are highly relevant to the healthcare industry
Guided by subject matter experts Michael DAndrea, Ivan Tarapov, Mazen Zawaideh, Nikhil Bikhchandani, and Emily Lindemer
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Applying AI to 3D Medical Imaging Data with these
activities:
Review Basic Concepts of 3D
Show steps
It will help you to understand the concepts used in the course.
Show steps
-
Revise the basics of linear algebra and calculus.
-
Review the basics of computer graphics.
-
Read about the basics of 3D imaging.
Help Other Students Learn About 3D Medical Imaging
Show steps
This will help you to solidify your understanding of the concepts and help others in the process.
Show steps
-
Join a study group or online forum.
-
Answer questions from other students.
-
Help to create or maintain resources for other students.
Solve Practice Problems Related to 3D Medical Imaging
Show steps
Practice problems can help you to improve your understanding of the concepts in the course.
Show steps
-
Find practice problems online or in textbooks.
-
Solve the problems and check your answers.
-
Review the solutions to the problems.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Review of 'Medical Image Computing' by N. Ayache
Show steps
Get an in-depth understanding of advanced medical image computing techniques, laying a solid foundation for the course.
View
Physics-Based Deformable Models: Applications...
on Amazon
Show steps
-
Read chapters 1-3 to gain a comprehensive overview of medical image computing concepts.
-
Focus on the sections covering 3D image representation and segmentation techniques.
-
Take notes and highlight important concepts for future reference.
Learn PyTorch and TensorFlow for 3D Medical Imaging
Show steps
PyTorch and TensorFlow are popular deep learning frameworks that are used extensively in 3D medical imaging.
Show steps
-
Follow a tutorial on PyTorch for 3D medical imaging.
-
Follow a tutorial on TensorFlow for 3D medical imaging.
-
Complete a project using PyTorch or TensorFlow for 3D medical imaging.
Solve practice exercises on medical image analysis
Show steps
Enhance your problem-solving skills by completing practice exercises related to medical image analysis.
Browse courses on
Medical Image Analysis
Show steps
-
Find practice problems online or in textbooks.
-
Work through the problems step-by-step.
-
Review your solutions and identify areas for improvement.
Segmentation and Classification Exercises on Medical Images
Show steps
Develop proficiency in applying segmentation and classification techniques to medical images, improving your hands-on skills.
Browse courses on
Image Segmentation
Show steps
-
Utilize online platforms or datasets to access medical image datasets.
-
Practice implementing segmentation algorithms using tools like SimpleITK or scikit-image.
-
Experiment with different classification models for medical image analysis.
Create a small-scale medical image segmentation project
Show steps
Apply your understanding of 3D medical imaging by building a project that segments medical images.
Browse courses on
Image Segmentation
Show steps
-
Choose a medical imaging dataset and define your segmentation task.
-
Select and train a deep learning model for image segmentation.
-
Evaluate the performance of your segmentation model.
-
Refine your model and explore additional features.
Explore Advanced Topics in Deep Learning for Medical Imaging
Show steps
Expand your knowledge of cutting-edge deep learning techniques for medical image analysis, complementing the course material.
Browse courses on
Deep Learning
Show steps
-
Identify reputable online courses or workshops on advanced deep learning topics.
-
Follow tutorials and complete assignments to gain practical experience.
-
Apply the learned techniques to real-world medical imaging datasets.
Develop a 3D Medical Image Visualization Tool
Show steps
Enhance your understanding of 3D medical image manipulation and visualization, reinforcing course concepts through practical application.
Browse courses on
3D Visualization
Show steps
-
Identify a framework or library for 3D medical image visualization.
-
Build a basic prototype to display and manipulate 3D medical images.
-
Incorporate image processing techniques for segmentation and analysis.
-
Create a user-friendly interface for interacting with the tool.
Build a 3D Medical Image Segmentation Model
Show steps
This will help you to develop a deeper understanding of the concepts involved in 3D medical image segmentation.
Show steps
-
Gather a dataset of 3D medical images.
-
Preprocess the images and segment them into different anatomical structures.
-
Train a machine learning model to perform the segmentation.
-
Evaluate the performance of the model and make improvements.
Follow tutorials on advanced medical imaging techniques
Show steps
Expand your knowledge of medical imaging by exploring advanced techniques through tutorials.
Show steps
-
Identify specific advanced techniques you want to learn.
-
Find high-quality tutorials or online courses on these techniques.
-
Follow the tutorials and complete the exercises.
Design and Build a Medical Image Analysis Pipeline
Show steps
Integrate concepts from the course into a comprehensive project, solidifying your understanding of medical image analysis workflow.
Browse courses on
Data Processing
Show steps
-
Define the scope and objectives of the pipeline.
-
Choose appropriate tools and technologies for each stage of the pipeline.
-
Implement data pre-processing, feature extraction, and model training modules.
-
Evaluate the performance of the pipeline and identify areas for improvement.
Contribute to Open-Source Projects in 3D Medical Imaging
Show steps
This will help you to gain experience with real-world 3D medical imaging projects.
Show steps
-
Identify an open-source project in 3D medical imaging that you are interested in.
-
Contribute to the project by fixing bugs, adding features, or writing documentation.
-
Collaborate with other contributors to the project.
Review Basic Concepts of 3D
Show steps
It will help you to understand the concepts used in the course.
Show steps
Show steps
Show steps
- Revise the basics of linear algebra and calculus.
- Review the basics of computer graphics.
- Read about the basics of 3D imaging.
Help Other Students Learn About 3D Medical Imaging
Show steps
This will help you to solidify your understanding of the concepts and help others in the process.
Show steps
Show steps
Show steps
- Join a study group or online forum.
- Answer questions from other students.
- Help to create or maintain resources for other students.
Solve Practice Problems Related to 3D Medical Imaging
Show steps
Practice problems can help you to improve your understanding of the concepts in the course.
Show steps
Show steps
Show steps
- Find practice problems online or in textbooks.
- Solve the problems and check your answers.
- Review the solutions to the problems.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Review of 'Medical Image Computing' by N. Ayache
Show steps
Get an in-depth understanding of advanced medical image computing techniques, laying a solid foundation for the course.
View
Physics-Based Deformable Models: Applications...
on Amazon
Show steps
Show steps
Show steps
- Read chapters 1-3 to gain a comprehensive overview of medical image computing concepts.
- Focus on the sections covering 3D image representation and segmentation techniques.
- Take notes and highlight important concepts for future reference.
Learn PyTorch and TensorFlow for 3D Medical Imaging
Show steps
PyTorch and TensorFlow are popular deep learning frameworks that are used extensively in 3D medical imaging.
Show steps
Show steps
Show steps
- Follow a tutorial on PyTorch for 3D medical imaging.
- Follow a tutorial on TensorFlow for 3D medical imaging.
- Complete a project using PyTorch or TensorFlow for 3D medical imaging.
Solve practice exercises on medical image analysis
Show steps
Enhance your problem-solving skills by completing practice exercises related to medical image analysis.
Browse courses on
Medical Image Analysis
Show steps
Show steps
Show steps
- Find practice problems online or in textbooks.
- Work through the problems step-by-step.
- Review your solutions and identify areas for improvement.
Segmentation and Classification Exercises on Medical Images
Show steps
Develop proficiency in applying segmentation and classification techniques to medical images, improving your hands-on skills.
Browse courses on
Image Segmentation
Show steps
Show steps
Show steps
- Utilize online platforms or datasets to access medical image datasets.
- Practice implementing segmentation algorithms using tools like SimpleITK or scikit-image.
- Experiment with different classification models for medical image analysis.
Create a small-scale medical image segmentation project
Show steps
Apply your understanding of 3D medical imaging by building a project that segments medical images.
Browse courses on
Image Segmentation
Show steps
Show steps
Show steps
- Choose a medical imaging dataset and define your segmentation task.
- Select and train a deep learning model for image segmentation.
- Evaluate the performance of your segmentation model.
- Refine your model and explore additional features.
Explore Advanced Topics in Deep Learning for Medical Imaging
Show steps
Expand your knowledge of cutting-edge deep learning techniques for medical image analysis, complementing the course material.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Identify reputable online courses or workshops on advanced deep learning topics.
- Follow tutorials and complete assignments to gain practical experience.
- Apply the learned techniques to real-world medical imaging datasets.
Develop a 3D Medical Image Visualization Tool
Show steps
Enhance your understanding of 3D medical image manipulation and visualization, reinforcing course concepts through practical application.
Browse courses on
3D Visualization
Show steps
Show steps
Show steps
- Identify a framework or library for 3D medical image visualization.
- Build a basic prototype to display and manipulate 3D medical images.
- Incorporate image processing techniques for segmentation and analysis.
- Create a user-friendly interface for interacting with the tool.
Build a 3D Medical Image Segmentation Model
Show steps
This will help you to develop a deeper understanding of the concepts involved in 3D medical image segmentation.
Show steps
Show steps
Show steps
- Gather a dataset of 3D medical images.
- Preprocess the images and segment them into different anatomical structures.
- Train a machine learning model to perform the segmentation.
- Evaluate the performance of the model and make improvements.
Follow tutorials on advanced medical imaging techniques
Show steps
Expand your knowledge of medical imaging by exploring advanced techniques through tutorials.
Show steps
Show steps
Show steps
- Identify specific advanced techniques you want to learn.
- Find high-quality tutorials or online courses on these techniques.
- Follow the tutorials and complete the exercises.
Design and Build a Medical Image Analysis Pipeline
Show steps
Integrate concepts from the course into a comprehensive project, solidifying your understanding of medical image analysis workflow.
Browse courses on
Data Processing
Show steps
Show steps
Show steps
- Define the scope and objectives of the pipeline.
- Choose appropriate tools and technologies for each stage of the pipeline.
- Implement data pre-processing, feature extraction, and model training modules.
- Evaluate the performance of the pipeline and identify areas for improvement.
Contribute to Open-Source Projects in 3D Medical Imaging
Show steps
This will help you to gain experience with real-world 3D medical imaging projects.
Show steps
Show steps
Show steps
- Identify an open-source project in 3D medical imaging that you are interested in.
- Contribute to the project by fixing bugs, adding features, or writing documentation.
- Collaborate with other contributors to the project.
Career center
Learners who complete Applying AI to 3D Medical Imaging Data will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers specializing in medical imaging are responsible for designing, developing, and deploying AI models for healthcare applications. This course provides a solid foundation in the fundamentals of AI for 3D medical imaging data, including deep neural network architectures and performance evaluation, which are essential skills for Machine Learning Engineers in this domain.
AI Software Engineer
AI Software Engineer
AI Software Engineers specializing in healthcare are responsible for designing, developing, and deploying AI solutions for healthcare applications. This course provides a solid foundation in the fundamentals of AI for 3D medical imaging data, including deep neural network architectures and performance evaluation, which are essential skills for AI Software Engineers in this domain.
Data Scientist
Data Scientist
Data Scientists with expertise in medical imaging are in high demand, as they can apply their skills to develop and deploy AI solutions for healthcare. This course provides a comprehensive overview of 3D medical imaging data, deep learning for image analysis, and clinical network integration, which are all valuable skills for Data Scientists in this field.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers specializing in healthcare are responsible for developing algorithms and systems for analyzing and interpreting medical images. This course provides a comprehensive overview of 3D medical imaging data, its formats, and analysis techniques, which are essential skills for Computer Vision Engineers in this domain.
Computational Imaging Scientist
Computational Imaging Scientist
Computational Imaging Scientists develop and apply computational techniques to improve the quality and interpretation of medical images. This course provides a comprehensive overview of 3D medical imaging data, its formats, and analysis techniques, which are essential skills for Computational Imaging Scientists.
Imaging Informatics Specialist
Imaging Informatics Specialist
Imaging Informatics Specialists are responsible for managing and analyzing medical imaging data, often using AI techniques. This course provides a comprehensive overview of 3D medical imaging data, its formats, and analysis techniques, which are essential skills for Imaging Informatics Specialists.
Radiologist
Radiologist
Radiologists specialize in diagnosing and treating diseases using medical imaging techniques. This course may be particularly relevant for Radiologists interested in leveraging AI-powered image analysis tools, as it provides insights into building and evaluating deep neural networks for 3D medical imaging.
Biomedical Engineer
Biomedical Engineer
Biomedical Engineers apply engineering principles to the development of medical technologies, including AI-powered image analysis tools. This course provides insights into the use of AI for 3D medical imaging data, which is an important area of research and development in biomedical engineering.
Clinical Research Scientist
Clinical Research Scientist
Clinical Research Scientists play a crucial role in evaluating the effectiveness and safety of new medical technologies, including AI-powered image analysis tools. This course may be useful in providing a deeper understanding of 3D medical imaging data and its analysis, which are essential for evaluating the performance of AI applications in clinical settings.
Health Informatics Specialist
Health Informatics Specialist
Health Informatics Specialists apply informatics principles to improve the management and use of health information, including medical images. This course may be useful in providing a deeper understanding of medical imaging data and its analysis, which are essential for Health Informatics Specialists in the healthcare industry.
Medical Physicist
Medical Physicist
Medical Physicists apply principles of physics to medicine, including the use of imaging technologies for diagnosis and treatment. This course may be useful in providing a foundational understanding of 3D medical imaging data and its analysis, which are essential aspects of medical physics.
Healthcare Data Analyst
Healthcare Data Analyst
Healthcare Data Analysts specialize in analyzing healthcare data to identify trends, patterns, and insights that can improve patient care. This course may be useful in providing a foundational understanding of 3D medical imaging data and its analysis, which are increasingly used in healthcare data analytics.
Healthcare IT Project Manager
Healthcare IT Project Manager
Healthcare IT Project Managers oversee the implementation and management of healthcare IT systems, including AI-powered image analysis tools. This course may be helpful in providing a foundational understanding of AI for 3D medical imaging data, which is increasingly used in healthcare IT systems.
Medical Imaging Analyst
Medical Imaging Analyst
A Medical Imaging Analyst plays an essential role in analyzing and interpreting medical images to identify and diagnose medical conditions. This course may be helpful in building a foundation for this role by providing an understanding of 3D medical imaging data, its formats, and analysis techniques commonly used in the field.
Medical Device Regulatory Affairs Specialist
Medical Device Regulatory Affairs Specialist
Medical Device Regulatory Affairs Specialists ensure that medical devices, including AI-powered image analysis tools, meet regulatory requirements for safety and effectiveness. This course may be useful in providing a deeper understanding of medical device regulation, which is essential for Medical Device Regulatory Affairs Specialists in the healthcare industry.
For more career information including salaries, visit:
OpenCourser.com/course/v8lzhg/applying
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Applying AI to 3D Medical Imaging Data.
Save
A comprehensive textbook that provides a deep dive into deep learning, covering fundamental concepts, architectures, and applications.
A widely-used textbook that provides a comprehensive foundation in statistical learning, including machine learning and data mining.
A comprehensive textbook that provides a foundation in pattern recognition and machine learning, covering supervised and unsupervised learning, and statistical models.
A comprehensive textbook that provides a foundation in information theory, inference, and learning algorithms, covering Bayesian networks, decision trees, and support vector machines.
Save
A comprehensive textbook that provides a foundation in computer vision, covering image processing, feature detection, and object recognition.
A comprehensive handbook that provides a comprehensive overview of computer science, including artificial intelligence, machine learning, and computer vision.
A textbook that provides a comprehensive overview of medical image analysis, including techniques for image segmentation, registration, and visualization.
A practical guide to deep learning for computer vision, covering image classification, object detection, and segmentation.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/v8lzhg/applying
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Similar courses
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Time
30240 hours
Level
Advanced
Via
Udacity
Instructors
Michael DAndrea
Ivan Tarapov
Mazen Zawaideh
Nikhil Bikhchandani
Emily Lindemer
Language
English
Good to know
Introduces core terminology of 3D medical imaging
Builds a solid foundation for beginners in 3D medical imaging
Teaches skills and knowledge that are highly relevant to the healthcare industry
Guided by subject matter experts Michael DAndrea, Ivan Tarapov, Mazen Zawaideh, Nikhil Bikhchandani, and Emily Lindemer
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