Semantic Brain Segmentation
A software development venture comprised of the intellectual property and knowledge of Andrew Abumoussa, MD as well as the technical expertise of our team of developers.
With the development of this software, we hope to contribute to the medical community at large by providing modern-day post-processing abilities to life-saving technologies such as MRI and CT scans.
There’s a very long tail of all sorts of creative products – beyond our core web search, image search and advertising businesses – that are powered by deep learning.
-Andrew Ng
We use machine learning as a tool to process radiographic images and classify their contents into useful, identifiable features that aid in a medical professional’s understanding of their patient.
The basis of this project is to construct a machine learning model that can quickly and accurately analyze and partition CT/MRI scans. While this may be a skill that surgeons can learn how to do quite quickly, our model is slightly more focused than this general use-case.
With the possibility of trauma to the skull and abnormal physiology, the everyday skills of the average medical professional are under much more pressure performing emergency surgery. This model is intended to aid in analyzing the physiology of the patient quickly. This can assist in making diagnostic decisions when preparing for such surgeries.
While the model is largely built to serve surgeons, given its interconnectivity with other modeling services provided by our client’s software, it may also find use in more general diagnostics.