Imagine a world where technology for humans doesn't require humans to operate. Where data is analyzed in industrial, automotive, and even medical settings by the machines themselves. And where factory line workers, long-haul truckers, and surgeons are not obsolete but more efficient and more capable than ever before.

As the nexus of human and cyber physical cognition, Machine Learning  systems are taking us into the fifth industrial revolution. And the Xilinx Vitis Unified Software Platform  is making it easier for companies to integrate Machine Learning features into their products.

The use of artificial intelligence (AI) – including machine learning (ML) and deep learning techniques (DL) is poised to become a transformational force in medical imaging. Patients, healthcare service providers, hospitals, professionals, and various stakeholders in the ecosystem all stand to benefit from ML driven tools. From anatomical geometric measurements to cancer detection, the possibilities are endless. In these scenarios, ML can lead to increased operational efficiencies and generate positive outcomes. 

There’s a broad spectrum of ways that ML can be used in medical imaging. For example, radiology, dermatology, vascular diagnostics, digital pathology and ophthalmology all use standard image processing techniques.