Deep Learning in Medical imaging
Transfer learning in medical imaging: classification and segmentation

Transfer learning in medical imaging: classification and segmentation

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?

Deep learning in MRI beyond segmentation: Medical image reconstruction, registration, and synthesis

Deep learning in MRI beyond segmentation: Medical image reconstruction, registration, and synthesis

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

Introduction to 3D medical imaging for machine learning: preprocessing and augmentations

Introduction to 3D medical imaging for machine learning: preprocessing and augmentations

Learn how to apply 3D transformations for medical image preprocessing and augmentation, to setup your awesome deep learning pipeline

Understanding coordinate systems and DICOM for deep learning medical image analysis

Understanding coordinate systems and DICOM for deep learning medical image analysis

Multiple introductory concepts regarding deep learning in medical imaging, such as coordinate system and dicom data extraction from the machine learning perspective.

Deep learning in medical imaging - 3D medical image segmentation with PyTorch

Deep learning in medical imaging - 3D medical image segmentation with PyTorch

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.