AIMC Topic: Diagnostic Imaging
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An East Coast Perspective on Artificial Intelligence and Machine Learning: Part 2: Ischemic Stroke Imaging and Triage.
Neuroimaging clinics of North America
Nov 1, 2020
Acute ischemic stroke constitutes approximately 85% of strokes. Most strokes occur in community settings; thus, automatic algorithms techniques are attractive for managing these cases. This article reviews the use of deep learning convolutional neura...
Outcomes of Adversarial Attacks on Deep Learning Models for Ophthalmology Imaging Domains.
JAMA ophthalmology
Nov 1, 2020
This study investigates whether adversarial attacks can confuse deep learning systems based on imaging domains.
Artificial intelligence and cardiovascular imaging: A win-win combination.
Anatolian journal of cardiology
Oct 1, 2020
Rapid development of artificial intelligence (AI) is gaining grounds in medicine. Its huge impact and inevitable necessity are also reflected in cardiovascular imaging. Although AI would probably never replace doctors, it can significantly support an...
Artificial intelligence in medical imaging: switching from radiographic pathological data to clinically meaningful endpoints.
The Lancet. Digital health
Sep 1, 2020
Artificial intelligence (AI) is a disruptive technology that involves the use of computerised algorithms to dissect complicated data. Among the most promising clinical applications of AI is diagnostic imaging, and mounting attention is being directed...
Fundamentals of artificial intelligence for ophthalmologists.
Current opinion in ophthalmology
Sep 1, 2020
PURPOSE OF REVIEW: As artificial intelligence continues to develop new applications in ophthalmic image recognition, we provide here an introduction for ophthalmologists and a primer on the mechanisms of deep learning systems.
Variability and Standardization of Quantitative Imaging: Monoparametric to Multiparametric Quantification, Radiomics, and Artificial Intelligence.
Investigative radiology
Sep 1, 2020
Radiological images have been assessed qualitatively in most clinical settings by the expert eyes of radiologists and other clinicians. On the other hand, quantification of radiological images has the potential to detect early disease that may be dif...
Prediagnostic Image Data, Artificial Intelligence, and Pancreatic Cancer: A Tell-Tale Sign to Early Detection.
Pancreas
Aug 1, 2020
Pancreatic cancer continues to be one of the deadliest malignancies and is the third leading cause of cancer-related mortality in the United States. Based on several models, it is projected to become the second leading cause of cancer-related deaths ...
Whole Slide Imaging (WSI) in Pathology: Current Perspectives and Future Directions.
Journal of digital imaging
Aug 1, 2020
Whole slide imaging (WSI), ever since its first introduction about two decades ago, has been validated for a number of applications in the field of pathology. The recent approval of US FDA to a WSI system for use in primary surgical pathology diagnos...
Enhanced Capsule Network for Medical image classification.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2020
Nowadays, cancer has become a major threat to people's lives and health. Convolutional neural network (CNN) has been used for cancer early identification, which cannot achieve the desired results in some cases, such as images with affine transformati...
AI in Medical Imaging Informatics: Current Challenges and Future Directions.
IEEE journal of biomedical and health informatics
Jul 1, 2020
This paper reviews state-of-the-art research solutions across the spectrum of medical imaging informatics, discusses clinical translation, and provides future directions for advancing clinical practice. More specifically, it summarizes advances in me...
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