Deep Learning with PyTorch for Medical Image Analysis

Learn how to use Pytorch-Lightning to solve real world medical imaging tasks!

4.65 (1001 reviews)

Udemy

platform

English

language

Data Science

What you will learn

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

Why take this course?

Did you ever want to apply Deep Neural Networks to more than MNIST, CIFAR10 or cats vs dogs?

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!

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Jose, Marcel, Sergios & Tobias

Screenshots

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Reviews

Danilo

August 28, 2023

This course is excellently instructed, clearly surpassing the typical quality of other courses on the platform. It provides lucid explanations that not only guide you through coding for specific tasks but also delve into the rationale behind the choices made.

Amit

June 28, 2023

This is one of the BEST courses I ever took up on Udemy. The concepts are quite advanced and the instructors do a fabulous job of explaining each project in detail. The projects are taken from Kaggle challenges which makes it even more interesting. All the basic tenets of computer vision like image classification, image detection and image segmentation have been covered really well. I had been looking for such a course for a long time. Absolutely loved this course and looking forward to other such high quality courses from this team. Would highly recommend this course to everyone :)

Khalid

June 7, 2023

Good , some of the programming concept need further explanation , testing for the models fitting need more explanation

Konstantinos

May 26, 2023

The course is good and is able to give good knowledge on image analysis using deep learning, as expected by the title. Nevertheless, it needs to be updated as there are several bugs in the codes, as well as some outdated use of libraries. That is the reason that I rate it as it could be better. If updated, it will be perfect.!

Pelin

April 23, 2023

I do not recommend for beginners!!! As I started to progress in the course, I began to have difficulty in understanding.

Hubert

March 25, 2023

A pneumonia detection classifier is not the same thing as a classifier of hot-dogs vs non hot-dogs. Bounding boxes were included in the dataset for a reason and discarding this information is an unacceptable if not dangerous over-simplification. A lot more hand-waving in the "medical" part of this course shows that the author isn't very competent.

Lead

January 11, 2023

I appreciate that the instructor likes to walk through writing each line of code, but I find that his explanations empty or missing altogether.

Bjørn

December 27, 2022

Hello, thanks for putting all the effort and dedication in this course. As a student in biomedical engineering with focus on AI, CV and imaging, this course was perfect to add practical implementation alongside with the theory from my lectures to my skill repertoire. I am very excited to be able to write my thesis on a medical imaging/ deep learning topic in a big MedTech company next year. For sure, a lot of knowledge (and code, haha) from this course will find its way into it. Big thanks and have a happy and succesfull new year 2023. Best, Bjørn from Lübeck/ Germany.

Chintamani

December 5, 2022

Another very good course by Jose on medical imaging analysis using Pytorch. Jose and Marcel has made this complex topic lot more interesting to learn step by step and has hige applications in Medical imaging industry .

Mahmoud

September 14, 2022

Jose is just reading the slides and one of the worst thing about him is that he doesn't update the content of his courses, Marcel is not a good choice at all as he is not able to deliver the information well and I really struggle to understand him.

Andrew

August 29, 2022

A very exciting course to learn about Medical Image Analysis using PyTorch. The concepts are well explained. It is very interesting and fascinating to learn this application of Deep Learning for Medical Image Analysis.

Ntk

July 6, 2022

big gap between introductory session and medical imaging section. Need to add more in bridging content.

Wade

June 5, 2022

The right amount of content, presented in the right order, taught in a clear and concise manner, by a very capable instructor.

Patrick

May 16, 2022

Towards the end the course becomes more and more of a code dump, with motivations poorly/not explained.

Bruce

April 17, 2022

Imprecise. For example, my course is deep learning with pytorch for medical image analysis, but your installation examples show pytorch boot camp as the installed code set (and directory).

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