AIMC Topic: Neuroimaging

Clear Filters Showing 461 to 470 of 903 articles

Updates on Deep Learning and Glioma: Use of Convolutional Neural Networks to Image Glioma Heterogeneity.

Neuroimaging clinics of North America
Deep learning represents end-to-end machine learning in which feature selection from images and classification happen concurrently. This articles provides updates on how deep learning is being applied to the study of glioma and its genetic heterogene...

Artificial Intelligence and Stroke Imaging: A West Coast Perspective.

Neuroimaging clinics of North America
Artificial intelligence (AI) advancements have significant implications for medical imaging. Stroke is the leading cause of disability and the fifth leading cause of death in the United States. AI applications for stroke imaging are a topic of intens...

Overview of Machine Learning: Part 2: Deep Learning for Medical Image Analysis.

Neuroimaging clinics of North America
Deep learning has contributed to solving complex problems in science and engineering. This article provides the fundamental background required to understand and develop deep learning models for medical imaging applications. The authors review the ma...

Brief History of Artificial Intelligence.

Neuroimaging clinics of North America
This article reviews the history of artificial intelligence and introduces the reader to major events that prompted interest in the field, as well as pitfalls and challenges that have slowed its development. The purpose of this article is to provide ...

Diverse Applications of Artificial Intelligence in Neuroradiology.

Neuroimaging clinics of North America
Recent advances in artificial intelligence (AI) and deep learning (DL) hold promise to augment neuroimaging diagnosis for patients with brain tumors and stroke. Here, the authors review the diverse landscape of emerging neuroimaging applications of A...

An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 1: Hemorrhagic Stroke Imaging and Triage.

Neuroimaging clinics of North America
Hemorrhagic stroke is a medical emergency. Artificial intelligence techniques and algorithms may be used to automatically detect and quantitate intracranial hemorrhage in a semiautomated fashion. This article reviews the use of deep learning convolut...

Knowledge Based Versus Data Based: A Historical Perspective on a Continuum of Methodologies for Medical Image Analysis.

Neuroimaging clinics of North America
The advent of big data and deep learning algorithms has promoted a major shift toward data-driven methods in medical image analysis recently. However, the medical image analysis field has a long and rich history inclusive of both knowledge-driven and...

Technologic Evolution of Navigation and Robotics in Spine Surgery: A Historical Perspective.

World neurosurgery
Spine surgery is continuously evolving. The synergy between medical imaging and advances in computation has allowed for stereotactic neuronavigation and its integration with robotic technology to assist in spine surgery. The discovery of x-rays in 18...

MRI-visible dilated perivascular spaces in healthy young adults: A twin heritability study.

Human brain mapping
We investigated the narrow-sense heritability of MRI-visible dilated perivascular spaces (dPVS) in healthy young adult twins and nontwin siblings (138 monozygotic, 79 dizygotic twin pairs, and 133 nontwin sibling pairs; 28.7 ± 3.6 years) from the Hum...

Transcranial MR Imaging-Guided Focused Ultrasound Interventions Using Deep Learning Synthesized CT.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Transcranial MR imaging-guided focused ultrasound is a promising novel technique to treat multiple disorders and diseases. Planning for transcranial MR imaging-guided focused ultrasound requires both a CT scan for skull densit...