Learn everything about one of the most famous convolutional neural network architectures that is widely used on image segmentation.
Find out the basics of CT imaging and segment lungs and vessels without labels with 3D medical image processing techniques.
What is transfer learning? How can it help us classify and segment different types of medical images? Are pretrained computer vision models useful for medical imaging tasks? How is 2D image classification different from 3D MRI segmentation in terms of transfer learning?
How can deep learning revolutionize medical image analysis beyond segmentation? In this article, we will see a couple of interesting applications in medical imaging such as medical image reconstruction, image synthesis, super-resolution, and registration in medical images
Learn how to apply 3D transformations for medical image preprocessing and augmentation, to setup your awesome deep learning pipeline
Multiple introductory concepts regarding deep learning in medical imaging, such as coordinate system and dicom data extraction from the machine learning perspective.
The basic MRI foundations are presented for tensor representation, as well as the basic components to apply a deep learning method that handles the task-specific problems(class imbalance, limited data). Moreover, we present some features of the open source medical image segmentation library. Finally, we discuss our preliminary experimental results and provide sources to find medical imaging data.