Kris T. Huang, MD, PhD, CTO

Innovation & Legacy

Global vs Local optimization


During a recent, socially distanced Pymedix corporate walking meeting outside in early January 2021, we discussed which company/companies were the most innovative personally. Perhaps predictably, companies like SpaceX, Tesla, and Apple were at the top of the list.

Besides innovation, what do these companies have in common? They all operate in safety-critical industries. SpaceX is aerospace, Tesla is automotive, and Apple entered the medical device industry in 2018 with the single-lead EKG feature in its Series 4 Apple Watch.

These industries come with a lot of technical legacy, and yet here we are with 3 wildly successful companies showing the old guard how innovation is done. SpaceX and Tesla in particular didn’t achieve their current success immediately, but they both began with a fresh approach that flew in the face of accepted legacy practice but proved to be correct.

The difference between leaps of innovation and incremental legacy improvement is the difference between global and local optimization. While global optimization still involves local optimization at some point, the difference is the goal, known in math, physics, and AI as the objective function.

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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”

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”