AIMC Topic: Diagnostic Imaging

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Quantifying uncertainty in machine learning classifiers for medical imaging.

International journal of computer assisted radiology and surgery Mar 12, 2022
PURPOSE: Machine learning (ML) models in medical imaging (MI) can be of great value in computer aided diagnostic systems, but little attention is given to the confidence (alternatively, uncertainty) of such models, which may have significant clinical...
Uncertainty Diagnostic Imaging Neural Networks, Computer Reproducibility of Results Machine Learning Humans
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Deep Correlated Joint Network for 2-D Image-Based 3-D Model Retrieval.

IEEE transactions on cybernetics Mar 11, 2022
In this article, we propose a novel deep correlated joint network (DCJN) approach for 2-D image-based 3-D model retrieval. First, the proposed method can jointly learn two distinct deep neural networks, which are trained for individual modalities to ...
Humans Diagnostic Imaging Models, Biological Deep Learning Algorithms
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Visual servoing of continuum robots: Methods, challenges, and prospects.

The international journal of medical robotics + computer assisted surgery : MRCAS Mar 7, 2022
BACKGROUND: Recent advancements in continuum robotics have accentuated developing efficient and stable controllers to handle shape deformation and compliance. The control of continuum robots (CRs) using physical sensors attached to the robot, particu...
Diagnostic Imaging Robotics Biomechanical Phenomena Humans
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Clinical Explainability Failure (CEF) & Explainability Failure Ratio (EFR) - Changing the Way We Validate Classification Algorithms.

Journal of medical systems Mar 5, 2022
Adoption of Artificial Intelligence (AI) algorithms into the clinical realm will depend on their inherent trustworthiness, which is built not only by robust validation studies but is also deeply linked to the explainability and interpretability of th...
Humans Radiography Diagnostic Imaging Algorithms Artificial Intelligence
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Machine Learning in Cardiovascular Imaging.

Heart failure clinics Mar 4, 2022
The number of cardiovascular imaging studies is growing exponentially, and so is the demand to improve the efficacy of the imaging workflow. Over the past decade, studies have demonstrated that machine learning (ML) holds promise to revolutionize car...
Cardiovascular System Diagnostic Imaging Machine Learning Humans
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Active label cleaning for improved dataset quality under resource constraints.

Nature communications Mar 4, 2022
Imperfections in data annotation, known as label noise, are detrimental to the training of machine learning models and have a confounding effect on the assessment of model performance. Nevertheless, employing experts to remove label noise by fully re...
Data Curation Benchmarking Delivery of Health Care Diagnostic Imaging Machine Learning
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Artificial Intelligence for Glaucoma: Creating and Implementing Artificial Intelligence for Disease Detection and Progression.

Ophthalmology. Glaucoma Feb 24, 2022
On September 3, 2020, the Collaborative Community on Ophthalmic Imaging conducted its first 2-day virtual workshop on the role of artificial intelligence (AI) and related machine learning techniques in the diagnosis and treatment of various ophthalmi...
Artificial Intelligence Humans Machine Learning Glaucoma Diagnostic Imaging Diagnostic Techniques, Ophthalmological
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Introducing and applying Newtonian blurring: an augmented dataset of 126,000 human connectomes at braingraph.org.

Scientific reports Feb 23, 2022
Gaussian blurring is a well-established method for image data augmentation: it may generate a large set of images from a small set of pictures for training and testing purposes for Artificial Intelligence (AI) applications. When we apply AI for non-i...
Electronic Data Processing Datasets as Topic Connectome Diagnostic Imaging Internet Image Processing, Computer-Assisted Humans Artificial Intelligence
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Non-radiologist perception of the use of artificial intelligence (AI) in diagnostic medical imaging reports.

Journal of medical imaging and radiation oncology Feb 21, 2022
INTRODUCTION: Incorporating artificial intelligence (AI) in diagnostic medical imaging reports has the potential to improve efficiency. Although perception of radiologists, radiographers, medical students and patients on AI use in image reporting has...
Humans Perception Diagnostic Imaging Radiologists Artificial Intelligence Radiology
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Practical Perfusion Quantification in Multispectral Endoscopic Video: Using the Minutes after ICG Administration to Assess Tissue Pathology.

AMIA ... Annual Symposium proceedings. AMIA Symposium Feb 21, 2022
The wide availability of near infrared light sources in interventional medical imaging stacks enables non-invasive quantification of perfusion by using fluorescent dyes, typically Indocyanine Green (ICG). Due to their often leaky and chaotic vasculat...
Indocyanine Green Diagnostic Imaging Humans Perfusion Fluorescent Dyes
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