Category: Pymedix
Kris T. Huang, MD, PhD, CTO
Make no mistake, neural networks are powerful tools. This class of algorithms single-handedly brought about drastic and rapid advancement in tasks like classification, speech recognition, and natural language processing, bringing about the end of the second “AI winter” that lasted from the late 1980s until around the late 2000s.
Sarah Kim, MD, CEO
At Pymedix, our goal is to advance cancer care for patients, and also physicians. As providers of medical care, Kris and I naturally want to make things better for our patients. As users of medical technology, we also want to make the tools we use better.
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.
Kris T. Huang, MD, PhD, CTO
The 1990s brought progress from chamfer matching to voxel intensity, and it ushered in the idea that intensity relationships between images could be non-linear, hinting at the concept of a more general dependence between images.
Continue reading “A Brief History of Image Registration: Part 3”
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”