Kris T. Huang, MD, PhD, CTO

Machine learning, and in particular so-called “deep learning,” is an undeniably powerful tool that has revolutionized certain types of classification problems, notably image/object recognition, speech recognition and synthesis, and automated language translation. The lay terms used in association with the field, like “neural,” “intelligence,” “deep,” and “learning,” evoke mental images of something brain-like or mind-like floating around in our computers, akin to an ancestor of HAL 9000. Combine these impressions with classification accuracies that rival or sometimes exceed human performance, and it is understandably convenient to ascribe human-like perceptual abilities to it.

Continue reading “Machine Learning Adversarial Attacks: It’s All Fun and Games Until Someone Gets Hurt”

Kris T. Huang, MD, PhD, CTO

Last time, we took a brief stroll through the timeline of radiology to take a look at the relationship between the evolution of imaging technologies and corresponding development in medical image registration. Digital radiology took root with the clinical introduction of CT in 1971, and despite the introduction of clinical MRI in 1980, it wasn’t until PET came of age in the early 1990s that the utility of image registration became plainly evident. Today we’ll dig into a couple of the early algorithms.

Continue reading “A Brief History of Image Registration: Part 2”

Kris T. Huang, MD, PhD, CTO

 

Have you ever wondered how far we’ve come in image registration technology? It wasn’t always the case that 3D deformable registration could be fully automated. This week, we’re throwing it back to 1895, when medical imaging started, then we’ll go back to the future to see how medical image registration evolved.

Continue reading “A Brief History of Image Registration: Part 1”