Efficient Medical Image Parsing
Florin C. Ghesu⁎,†; Bogdan Georgescu⁎; Joachim Hornegger† ⁎Siemens Medical Solutions USA, Inc., Princeton, NJ, United States†Friedrich-Alexander University Erlangen–Nürnberg, Erlangen, Germany
Abstract
Fast and robust detection, segmentation and tracking of anatomical structures or pathologies support the entire clinical workflow enabling real-time guidance, quantification, and processing in the operating room. Most state-of-the-art solutions for parsing medical images are based on machine learning methods. While this enables the effective use of large annotated image databases, such techniques typically suffer from inherent limitations related to the efficiency in scanning high-dimensional ...
Get Deep Learning for Medical Image Analysis now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
