Deep Learning with PyTorch for Medical Image Analysis from Udemy

Did you ever want to apply Deep Neural Networks to more than

Do you want to learn about state of the art Machine Learning frameworks while segmenting cancer in CT-images?

Then this is the right course for you.

Welcome to one of the most comprehensive courses on Deep Learning in medical imaging.

This course focuses on the application of state of the art Deep Learning architectures to various medical imaging challenges.

You will tackle several different tasks, including cancer segmentation, pneumonia classification, cardiac detection, Interpretability and many more.

The following topics are covered:

NumPy
Machine Learning Theory
Test/Train/Validation Data Splits
Model Evaluation - Regression and Classification Tasks
Tensors with PyTorch
Convolutional Neural Networks
Medical Imaging
Interpretability of a network's decision - Why does the network do what it does?
A state of the art high level pytorch library: pytorch-lightning
Tumor Segmentation
Three-dimensional data
and many more

Why choose this specific Deep Learning with PyTorch for Medical Image Analysis course ?

This course provides unique knowledge on the application of deep learning to highly complex and non-standard (medical) problems (in 2D and 3D)
All lessons include clearly summarized theory and code-along examples, so that you can understand and follow every step.
Powerful online community with our QA Forums with thousands of students and dedicated Teaching Assistants, as well as student interaction on our Discord Server.
You will learn skills and techniques that the vast majority of AI engineers do not have.

Jose, Marcel, Sergios & Tobias

What's inside

Learning objectives

Learn how to use numpy
Learn classic machine learning theory principals
Foundations of medical imaging
Data formats in medical imaging
Creating artificial neural networks with pytorch

Use pytorch-lightning for state of the art training
Visualize the decision of a cnn
2d & 3d data handling
Automatic cancer segmentation

Learn how to use numpy
Learn classic machine learning theory principals
Foundations of medical imaging
Data formats in medical imaging
Creating artificial neural networks with pytorch
Use pytorch-lightning for state of the art training
Visualize the decision of a cnn
2d & 3d data handling
Automatic cancer segmentation

Syllabus

Introduction

COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP!

Link to Download the Course Files

Installation and Environment Setup

Installation without yml file

Course Curriculum

Crash Course: NumPy

Introduction to NumPy

NumPy Arrays

NumPy Arrays Part Two

NumPy Index Selection

NumPy Operations

NumPy Exercises

NumPy Exercise - Solutions

Machine Learning Concepts Overview

What is Machine Learning

Supervised Learning

Overfitting

Evaluating Performance - Classification Error Metrics

Evaluating Performance - Regression Error Metrics

Recap: Machine Learning Concepts

PyTorch Basics

PyTorch Basics Introduction

Tensor Basics

Tensor Basics-Part Two

Tensor Operations

Tensor Operations-Part Two

PyTorch Basics - Exercise

PyTorch Basics - Exercise Solutions

CNN - Convolutional Neural Networks

Introduction to CNNs

Understanding the MNIST data set

ANN with MNIST - Part One - Data

ANN with MNIST - Part Two - Creating the Network

IMPORTANT: Library Difference between video and notebook

ANN with MNIST - Part Three - Training

ANN with MNIST - Part Four - Evaluation

Image Filters and Kernels

Convolutional Layers

Pooling Layers

MNIST Data Revisited

MNIST with CNN - Code Along - Part One

MNIST with CNN - Code Along - Part Two

MNIST with CNN - Code Along - Part Three

Why do we need GPUs?

Using GPUs for PyTorch

Medical Imaging - A short Introduction

Overview: X-RAY

Overview: CT

Overview: MRI

Overview: PET

Recap: Medical Imaging

ToDO

DICOM

DICOM-in-Python

Recap: DICOM

NIfTI

NIfTI-in-Python

Recap:NIfTI

Preprocessing

Preprocessing-in-Python-Part-1

Preprocessing-in-Python-Part-2

Recap: Preprocessing

Build a deep learning model which is able to classify whether an x-ray image contains a pneumonia or not

Train-01-Data-Loading

Train-02-Model-Creation

Train-03-Trainer

Train-04-Evaluation

Interpretability

Recap: Pneumonia-Classification

Cardiac-Detection

01-Introduction

02-Preprocessing

03-Dataset-Part-1

04-Dataset-Part-2

Train-03-Evaluation

Atrium-Segmentation

Preprocessing-01-Visualization

Preprocessing-02-Processing

Dataset-01-Dataset-Creation

Dataset-02-Dataset-Validation

UNet

Train-01-Data-Loading-and-Loss

Capstone-Project: Lung Tumor Segmentation

Overview

Oversampling

Hint - RuntimeError: expected scalar type Double but found Float

Discussion

3D Liver and Liver Tumor Segmentation

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by experts in the field of medical image analysis, such as Jose Portilla and Marcel Früh

Develops advanced AI engineering knowledge and skills that are in high demand across industries

Strong focus on practical implementation with hands-on coding exercises

Provides comprehensive coverage of Deep Learning architectures and techniques

Course materials and resources are well-structured and easy to follow

Prerequisites include basic programming skills and probability theory knowledge

Reviews summary

Well-received medical imaging course

Learners say this well-structured course on deep learning for medical image analysis is well-received. With engaging lectures and examples, even beginners find this easy to understand. Students especially appreciate the instructor's clear and detailed teaching style.

Suitable for learners of all levels.

"Loved the course. It was easy to learn as Iam beginner"

"Easy to understand for beginners."

"I am a total beginner and the explanations are great"

Mostly positive reviews.

"amazing I've learnt so much so far"

"Very insightful."

"Absolutely Amazing! Love how Sal is so detailed"

"perfect match for me and best decission"

Course is well-organized and easy to follow.

"It was great course for beginners. simple to follow"

"I like the way the course is set up."

"Sal Jade teaches every aspect of the deck, leaving nothing out"

Instructor is clear and detailed.

"The course is good, profound knowledge."

"it is absolutely great!"

"Sal's background as a teacher really shows"

"I appreciate the instructors intuitiveness and incredible amount of knowledge."

Informative and engaging content.

"easy to understand and lots of examples"

"very interesting, easy to follow, easy to understand"

"less things to read and many lectures as videos"

"Super informative AND actually taught from the heart"

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 Deep Learning with PyTorch for Medical Image Analysis with these activities:

Study Group

Show steps

Collaborate with peers to discuss course material, ask questions, and reinforce your understanding.

Show steps

Form a study group with 2-3 classmates.
Meet regularly to discuss course content and assignments.
Take turns presenting key concepts to the group.

Organize study materials

Show steps

Organizing notes, assignments, and quizzes helps you prepare for the course.

Show steps

Gather course materials including notes, assignments, and quizzes
Organize materials chronologically by topic or date
Review materials to familiarize yourself with key concepts

Organize study groups or discussion forums with classmates

Show steps

Engaging with peers will enhance your understanding through shared perspectives, discussions, and collaborative problem-solving.

Show steps

Connect with fellow students taking the course
Establish regular meetings for group discussions or study sessions

14 other activities

Expand to see all activities and additional details

Show all 17 activities

Foundations of Artificial Neural Networks

Show steps

Review the foundational concepts of ANNs to help solidify and build upon your understanding of the course materials.

View Deep Learning (Adaptive Computation and Machine... on Amazon

Show steps

Read Chapters 1-3 of the book.
Take notes on the key concepts and definitions.
Complete the practice exercises at the end of each chapter.

Revisit the basics of NumPy

Show steps

Familiarizing yourself with NumPy's core concepts and operations will enhance your understanding of the course material.

Browse courses on NumPy

Show steps

Review the documentation on NumPy's website
Work through a tutorial or online course on NumPy

PyTorch Tutorial for Beginners

Show steps

Follow a guided tutorial to gain hands-on experience with PyTorch, the framework used in the course.

Browse courses on PyTorch

Show steps

Find a beginner-friendly PyTorch tutorial online.
Follow the tutorial step-by-step.
Run the code examples provided in the tutorial.

Complete practice problems

Show steps

Practice can help deepen your understanding of concepts and improve your ability to apply them.

Show steps

Identify areas where you need more practice
Find practice problems online or in textbooks
Set aside time to work on practice problems
Review your answers and identify areas for improvement

Medical Image Classification Practice

Show steps

Practice classifying medical images to strengthen your understanding of the techniques used in the course.

Browse courses on Image Recognition

Show steps

Find a dataset of medical images.
Load the dataset into your preferred programming environment.
Build a model to classify the images.

Practice building and training simple neural networks

Show steps

Hands-on practice in constructing and training neural networks will solidify your grasp of the fundamental principles.

Browse courses on Neural Networks

Show steps

Follow along with the course tutorials on building and training neural networks in PyTorch
Work through additional exercises or projects involving neural network development

Develop a summary or tutorial on a specific course topic

Show steps

Creating content will reinforce your understanding, improve your communication skills, and potentially benefit others.

Show steps

Choose a specific topic from the course material
Research and gather information on the topic
Organize and write your summary or tutorial

Connect with experienced professionals in the field of medical imaging

Show steps

Seeking guidance from experts will provide valuable insights, expand your network, and facilitate your professional growth.

Show steps

Attend industry events or conferences related to medical imaging
Reach out to professors, researchers, or practitioners in the field

Cancer Segmentation Project

Show steps

Develop a model to segment cancer in medical images, applying the techniques learned in the course.

Show steps

Gather a dataset of medical images containing cancer.
Preprocess the images to prepare them for training.
Train a model to segment the cancer.
Evaluate the performance of the model.

Explore advanced topics in PyTorch-Lightning

Show steps

Delving deeper into PyTorch-Lightning's capabilities will equip you with tools for efficient and effective model training.

Show steps

Review the official PyTorch-Lightning documentation
Follow along with tutorials or workshops on advanced PyTorch-Lightning techniques

Contribute to PyTorch

Show steps

Engage with the PyTorch community and contribute to its development.

Browse courses on PyTorch

Show steps

Find an issue or feature request on the PyTorch GitHub repository.
Fork the repository and make changes to address the issue or implement the feature.
Create a pull request to merge your changes back into the main branch.

Participate in hackathons or competitions focused on medical imaging

Show steps

Engaging in competitive events will challenge your knowledge, foster teamwork, and expose you to cutting-edge advancements.

Show steps

Research and identify upcoming hackathons or competitions
Form a team or collaborate with other participants
Develop and submit a project that addresses the competition's goals

Volunteer at a medical imaging facility or research center

Show steps

Practical experience in a medical imaging setting will provide valuable context and insights beyond the classroom.

Browse courses on Medical Imaging

Show steps

Identify local medical imaging facilities or research centers
Inquire about volunteer opportunities and requirements
Attend volunteer training and orientations

Develop a medical imaging project using the course concepts

Show steps

Applying your acquired knowledge to a real-world project will enhance your comprehension and practical skills.

Browse courses on Medical Imaging

Show steps

Identify a medical imaging problem or dataset to work on
Design and implement a deep learning model to address the problem
Train and evaluate the model using the provided dataset

Career center

Learners who complete Deep Learning with PyTorch for Medical Image Analysis will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

A Machine Learning Engineer designs, builds, tests, deploys, manages, and maintains machine learning models. This course can help you develop the skills needed to build and deploy machine learning models for medical image analysis. The course covers topics such as machine learning theory, deep learning, and medical imaging, which are all essential for a Machine Learning Engineer working in the field of medical image analysis.

See salaries and explore the career path for Machine Learning Engineer

Medical Imaging Analyst

A Medical Imaging Analyst designs, builds, tests, deploys, manages, and maintains medical imaging software and systems. This course can help you gain knowledge about the underlying principles of medical imaging, which could be helpful for developing and maintaining medical imaging software and systems. The course also covers topics such as data formats in medical imaging, which is important for understanding how medical images are stored and processed.

See salaries and explore the career path for Medical Imaging Analyst

Data Scientist

A Data Scientist analyzes data to extract insights and build predictive models. This course can help you develop the skills needed to analyze medical imaging data. The course covers topics such as data preprocessing, feature engineering, and model evaluation, which are all essential for a Data Scientist working in the field of medical image analysis.

See salaries and explore the career path for Data Scientist

Medical Physicist

A Medical Physicist applies the principles of physics to medicine. This course can help you gain knowledge about the underlying principles of medical imaging, which could be helpful for developing and maintaining medical imaging equipment. The course also covers topics such as radiation safety and quality assurance, which are important for ensuring the safe and effective use of medical imaging equipment.

See salaries and explore the career path for Medical Physicist

Radiologist

A Radiologist interprets medical images to diagnose and treat diseases. This course can help you gain knowledge about the underlying principles of medical imaging, which could be helpful for interpreting medical images more accurately. The course also covers topics such as anatomy and physiology, which are important for understanding the human body and how it functions.

See salaries and explore the career path for Radiologist

Ultrasound Technologist

An Ultrasound Technologist performs ultrasound procedures and analyzes the results. This course can help you gain knowledge about the underlying principles of medical imaging, which could be helpful for performing ultrasound procedures more accurately. The course also covers topics such as anatomy and physiology, which are important for understanding the human body and how it functions.

See salaries and explore the career path for Ultrasound Technologist

Radiation Therapist

A Radiation Therapist delivers radiation therapy to patients with cancer. This course can help you gain knowledge about the underlying principles of medical imaging, which could be helpful for planning and delivering radiation therapy more accurately. The course also covers topics such as radiation safety and quality assurance, which are important for ensuring the safe and effective use of radiation therapy equipment.

See salaries and explore the career path for Radiation Therapist

Nuclear Medicine Technologist

A Nuclear Medicine Technologist performs nuclear medicine procedures and analyzes the results. This course can help you gain knowledge about the underlying principles of medical imaging, which could be helpful for performing nuclear medicine procedures more accurately. The course also covers topics such as radiation safety and quality assurance, which are important for ensuring the safe and effective use of nuclear medicine equipment.

See salaries and explore the career path for Nuclear Medicine Technologist

Biomedical Engineer

A Biomedical Engineer designs, builds, tests, deploys, manages, and maintains medical devices and systems. This course can help you develop the skills needed to design and develop medical imaging devices and systems. The course covers topics such as medical imaging, signal processing, and embedded systems, which are all essential for a Biomedical Engineer working in the field of medical image analysis.

See salaries and explore the career path for Biomedical Engineer

Healthcare Consultant

A Healthcare Consultant provides consulting services to healthcare providers. This course can help you gain knowledge about the underlying principles of medical imaging, which could be helpful for providing consulting services to healthcare providers on the use of medical imaging. The course also covers topics such as healthcare economics and policy, which are important for understanding the healthcare industry and how to provide consulting services to healthcare providers.

See salaries and explore the career path for Healthcare Consultant

Medical Device Sales Representative

A Medical Device Sales Representative sells medical devices and systems to healthcare providers. This course can help you gain knowledge about the underlying principles of medical imaging, which could be helpful for selling medical imaging devices and systems more effectively. The course also covers topics such as healthcare economics and marketing, which are important for understanding the healthcare industry and how to market medical devices and systems.

See salaries and explore the career path for Medical Device Sales Representative

Clinical Research Coordinator

A Clinical Research Coordinator manages clinical trials. This course can help you gain knowledge about the underlying principles of medical imaging, which could be helpful for designing and managing clinical trials that involve medical imaging. The course also covers topics such as clinical trial design and data management, which are important for understanding how to conduct clinical trials and manage clinical data.

See salaries and explore the career path for Clinical Research Coordinator

Science Writer

A Science Writer writes about science and technology for a variety of audiences. This course can help you gain knowledge about the underlying principles of medical imaging, which could be helpful for writing about medical imaging for a variety of audiences. The course also covers topics such as scientific writing and journalism, which are important for understanding how to write about science and technology.

See salaries and explore the career path for Science Writer

Patent Attorney

A Patent Attorney prepares and prosecutes patent applications. This course may be useful for understanding the underlying principles of medical imaging, which could be helpful for preparing and prosecuting patent applications for medical imaging devices and systems.

See salaries and explore the career path for Patent Attorney

Technical Writer

A Technical Writer writes technical documentation. This course may be useful for understanding the underlying principles of medical imaging, which could be helpful for writing technical documentation for medical imaging devices and systems.

See salaries and explore the career path for Technical Writer