[1] Martin Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek G. Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, Xiaoqiang Zheng, and Google Brain. Tensorflow: A system for largescale machine…… Continue reading References
Category: Kappa
Part III: The role of machine learning in medical imaging
ML has shown promise for a wide range of applications in the field of medicine due to its ability to process and analyze large volumes of data in a relatively short amount of time [69]. Today, medical data is being generated at an unprecedented rate, providing further incentive towards the use of ML, which has…… Continue reading Part III: The role of machine learning in medical imaging
Part II: Imaging in Radiotherapy
Several imaging modalities have been developed with the aim to acquire signal from different physical properties of the scanned anatomy, providing functional (e.g. PET, SPECT) or structural information (e.g. MRI, CT). Their signals complement each other, therefore it is becoming common for radiotherapy treatment to involve a combination of modalities. This provides more information about…… Continue reading Part II: Imaging in Radiotherapy
Part I: Machine Learning Basics
ML is a subset of the huge field of Artificial Intelligence (AI) recentlyproving very effective especially at relatively simple, but time consuming tasks. The relevant subsets of AI are collected in Figure 2.1. Examples and effective applications are truly wide-spread, ranging from faster matrix multiplications [35], to tracking the movements of mobile phone users using…… Continue reading Part I: Machine Learning Basics
Demo: MRI contrast
Demo post for the MRI spin-echo signal equation.