AIMC Topic: Image Interpretation, Computer-Assisted
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Precision of artificial intelligence in paediatric cardiology multimodal image interpretation.
Cardiology in the young
Nov 11, 2024
Multimodal imaging is crucial for diagnosis and treatment in paediatric cardiology. However, the proficiency of artificial intelligence chatbots, like ChatGPT-4, in interpreting these images has not been assessed. This cross-sectional study evaluates...
Weakly Supervised Classification of Mohs Surgical Sections Using Artificial Intelligence.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Nov 9, 2024
Basal cell carcinoma (BCC) is the most frequently diagnosed form of skin cancer, and its incidence continues to rise, particularly among older individuals. This trend puts a significant strain on health care systems, especially in terms of histopatho...
Fusing global context with multiscale context for enhanced breast cancer classification.
Scientific reports
Nov 9, 2024
Breast cancer is the second most common type of cancer among women. Prompt detection of breast cancer can impede its advancement to more advanced phases, thereby elevating the probability of favorable treatment consequences. Histopathological images ...
Automated assessment of brain MRIs in multiple sclerosis patients significantly reduces reading time.
Neuroradiology
Nov 8, 2024
INTRODUCTION: Assessment of multiple sclerosis (MS) lesions on magnetic resonance imaging (MRI) is tedious, time-consuming, and error-prone. We evaluate whether assessment of new, expanding, and contrast-enhancing MS lesions can be done more time-eff...
Joint suppression of cardiac bSSFP cine banding and flow artifacts using twofold phase-cycling and a dual-encoder neural network.
Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
Nov 7, 2024
BACKGROUND: Cardiac balanced steady state free precession (bSSFP) cine imaging suffers from banding and flow artifacts induced by off-resonance. The work aimed to develop a twofold phase cycling sequence with a neural network-based reconstruction (2P...
Deep learning automatically distinguishes myocarditis patients from normal subjects based on MRI.
The international journal of cardiovascular imaging
Nov 7, 2024
Myocarditis, characterized by inflammation of the myocardial tissue, presents substantial risks to cardiovascular functionality, potentially precipitating critical outcomes including heart failure and arrhythmias. This investigation primarily aims to...
Image quality in three-dimensional (3D) contrast-enhanced dynamic magnetic resonance imaging of the abdomen using deep learning denoising technique: intraindividual comparison between T1-weighted sequences with compressed sensing and with a modified Fast 3D mode wheel.
Japanese journal of radiology
Nov 6, 2024
PURPOSE: To assess the image quality of a modified Fast three-dimensional (Fast 3D) mode wheel with sequential data filling (mFast 3D wheel) combined with a deep learning denoising technique (Advanced Intelligent Clear-IQ Engine [AiCE]) in contrast-e...
Deep Interactive Segmentation of Medical Images: A Systematic Review and Taxonomy.
IEEE transactions on pattern analysis and machine intelligence
Nov 6, 2024
Interactive segmentation is a crucial research area in medical image analysis aiming to boost the efficiency of costly annotations by incorporating human feedback. This feedback takes the form of clicks, scribbles, or masks and allows for iterative r...
TPAFNet: Transformer-Driven Pyramid Attention Fusion Network for 3D Medical Image Segmentation.
IEEE journal of biomedical and health informatics
Nov 6, 2024
The field of 3D medical image segmentation is witnessing a growing trend in the utilization of combined networks that integrate convolutional neural networks and transformers. Nevertheless, prevailing hybrid networks are confronted with limitations i...
Classification of Multi-Parametric Body MRI Series Using Deep Learning.
IEEE journal of biomedical and health informatics
Nov 6, 2024
Multi-parametric magnetic resonance imaging (mpMRI) exams have various series types acquired with different imaging protocols. The DICOM headers of these series often have incorrect information due to the sheer diversity of protocols and occasional t...
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