This course for computer scientists and professionals starting their journey in image analysis algorithm development for digital pathology will help you understand tissue and develop better algorithms faster, accelerate your research, and ultimately benefit the patients without the necessity to deeply understand medicine.
Aleksandra Zuraw is a board-certified veterinary pathologist with over a decade of experience in the digital pathology space. Her vision is to build a bridge between all stakeholders of the digital pathology ecosystem and make the world of digital pathology a more accessible place. She is an in person and online digital pathology educator and wants you to be a huge success in this space as well! Taking each and every course and online resource she creates is your step towards that success! We are so happy you are here with us! Welcome fellow digital pathology trailblazer!
Pathology can be intimidating, especially when you think how many years pathologists study to get specialized. This module is about the right mindset that wil help you assimilate the knowledge provided in this course and have fun with it!
Learn what happens with the tissue sample from the moment when it is excised from the body to the moment of being ready to be evaluated by a pathologist under the microscope; variables that might affect the future tissue image quality, leading to the digitization of glass slides and creation of whole slide images.
Learn about the most popular pathology stain used for initial evaluation of every pathology sample (hematoxylin & eosin), the chemical special stains that mark specific tissue elements with different colors and the principles of IHC, and what factors influence the appearance of the final IHC stained slide.
Tissue image analysis applies the principles of computer vision to solving pathology problems. Learn which computer vision tasks are most appropriate for which pathology problems. Know when it makes sense to use object detection, semantic segmentation and when instance segmentation is the best choice.
Pathology as any medical specialty uses specific terminology. If you are working closely with a pathologist, the key to good communication is being familiar with this technology. This is exactly what you will learn in this module.
In this module you will learn how to distinguish tumor from non-neoplastic tissue, what the different types of tissue are and how to distinguish them, which entities fall into the epithelial category, and the different immune cell players as well as other components of the tumor microenvironment.
Dead tissue is called necrosis. It differs chemically and visually from living tissue. In this modules we will learn about the appearance of necrotic tissue and how to avoid the pitfalls caused by necrosis.
In this bonus module I walk you through 10 best external resources that will help you complement the knowledge acquired in this course and make you a tissue image analysis pro.