Computer Vision
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

Self-supervised representation learning on videos

Self-supervised representation learning on videos

In this article, we dive into the state-of-the-art methods on self-supervised representation learning in computer vision, by carefully reviewing the fundamentals concepts of self-supervision on learning video representations.

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.

Deepfakes: Face synthesis with GANs and Autoencoders

Deepfakes: Face synthesis with GANs and Autoencoders

A closer look on Deepfakes: face sythesis with StyleGAN, face swap with XceptionNet and facial attributes and expression manipulation with StarGAN

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.

Human Pose Estimation

Human Pose Estimation

An overview of the most popular models for performing 2D or 3D Human Pose Estimation

YOLO - You only look once (Single shot detectors)

YOLO - You only look once (Single shot detectors)

Single shot detectors and how YOLO is used for object detection and localization

Localization and Object Detection with Deep Learning

Localization and Object Detection with Deep Learning

Explain RCNN, Fast RCNN and Faster RCNN

Semantic Segmentation in the era of Neural Networks

Semantic Segmentation in the era of Neural Networks

Semantic segmentation with deep learning

How to Generate Images using Autoencoders

How to Generate Images using Autoencoders

Learn what autoencoders are and build one to generate new images

Self-driving cars using Deep Learning

Self-driving cars using Deep Learning

How self driving cars work, why Deep Learning made them a reality and how to program one (sort of)