Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2023
In brain imaging research, it is becoming standard practice to remove the face from the individual's 3D structural MRI scan to ensure data privacy standards are met. Face removal - or 'defacing' - is being advocated for large, multi-site studies wher...
AIM: To identify the most influential publications relating to artificial intelligence (AI) in radiology in order to identify current trends in the literature and to highlight areas requiring further research.
Advances in experimental medicine and biology
Jan 1, 2023
In biomedical machine learning, data often appear in the form of graphs. Biological systems such as protein interactions and ecological or brain networks are instances of applications that benefit from graph representations. Geometric deep learning i...
In mental state decoding, researchers aim to identify the set of mental states (e.g., experiencing happiness or fear) that can be reliably identified from the activity patterns of a brain region (or network). Deep learning (DL) models are highly prom...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2022
Deep learning algorithms for predicting from neuroimaging data have shown considerable promise. Deep learning models that take advantage of the data's 3D structure have been proven to outperform ordinary machine learning on a number of learning tasks...
BACKGROUND: Intracranial hemorrhage (ICH) is considered an emergency that requires rapid medical or surgical management. Previous studies have used artificial intelligence to attempt to expedite the diagnosis of this pathology on neuroimaging. Howeve...
Deep-brain microscopy is strongly limited by the size of the imaging probe, both in terms of achievable resolution and potential trauma due to surgery. Here, we show that a segment of an ultra-thin multi-mode fiber (cannula) can replace the bulky mic...
This chapter describes technical considerations and current and future clinical applications of lesion detection using machine learning in the clinical setting. Lesion detection is central to neuroradiology and precedes all further processes which in...
In this chapter, we describe the process of obtaining medical imaging data and its storage protocol. The authors also explain in a step-by-step approach how to extract and prepare the medical imaging data for machine learning algorithms. And finally,...
Advancements in neuroimaging and the availability of large-scale datasets enable the use of more sophisticated machine learning algorithms. In this chapter, we non-exhaustively discuss relevant analytical steps for the analysis of neuroimaging data u...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.