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"

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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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