Foreword
This issue of Neuroimaging Clinics focuses on the fascinating field of functional MR imaging (fMR imaging). I remember my complete amazement when I first saw the brain “think” on MR images. One of the fun things I routinely do is give a talk to a high-school anatomy class on neuroradiology, and it is really cool to see their excitement when I show the fMR images. (Source: Neuroimaging Clinics)
Source: Neuroimaging Clinics - October 28, 2020 Category: Radiology Authors: Suresh K. Mukherji Source Type: research
Review of Natural Language Processing in Radiology
Natural language processing (NLP) is an interdisciplinary field, combining linguistics, computer science, and artificial intelligence to enable machines to read and understand human language for meaningful purposes. Recent advancements in deep learning have begun to offer significant improvements in NLP task performance. These techniques have the potential to create new automated tools that could improve clinical workflows and unlock unstructured textual information contained in radiology and clinical reports for the development of radiology and clinical artificial intelligence applications. These applications will combine...
Source: Neuroimaging Clinics - October 8, 2020 Category: Radiology Authors: Jack W. Luo, Jaron J.R. Chong Source Type: research
An East Coast Perspective on Artificial Intelligence and Machine Learning
This article reviews the use of deep learning convolutional neural networks in the management of ischemic stroke. Artificial intelligence-based algorithms may be used in patient triage to detect and sound the alarm based on early imaging, alert care teams, and assist in treatment selection. This article reviews algorithms for artificial intelligence techniques that may be used to detect and localize acute ischemic stroke. We describe artificial intelligence algorithms for these tasks and illustrate them with examples. (Source: Neuroimaging Clinics)
Source: Neuroimaging Clinics - October 8, 2020 Category: Radiology Authors: Rajiv Gupta, Sanjith Prahas Krishnam, Pamela W. Schaefer, Michael H. Lev, R. Gilberto Gonzalez Source Type: research
Machine Learning Applications for Head and Neck Imaging
This article reviews the recent applications of machine learning (ML) in HN imaging with a focus on deep learning approaches. It categorizes ML applications in HN imaging into deep learning and traditional ML applications and provides examples of each category. It also discusses the main challenges facing the successful deployment of ML-based applications in the clinical setting and provides suggestions for addressing these challenges. (Source: Neuroimaging Clinics)
Source: Neuroimaging Clinics - October 8, 2020 Category: Radiology Authors: Farhad Maleki, William Trung Le, Thiparom Sananmuang, Samuel Kadoury, Reza Forghani Source Type: research
Machine Learning Algorithm Validation
This article describes the fundamental concepts and processes for ML model evaluation and highlights common workflows. It concludes with a discussion of the requirements for the deployment of ML models in clinical settings. (Source: Neuroimaging Clinics)
Source: Neuroimaging Clinics - October 8, 2020 Category: Radiology Authors: Farhad Maleki, Nikesh Muthukrishnan, Katie Ovens, Caroline Reinhold, Reza Forghani Source Type: research
