AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Imaging, Three-Dimensional

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The accuracy of automated facial landmarking - a comparative study between Cliniface software and patch-based Convoluted Neural Network algorithm.

European journal of orthodontics
BACKGROUND: Automatic landmarking software packages simplify the analysis of the 3D facial images. Their main deficiency is the limited accuracy of detecting landmarks for routine clinical applications. Cliniface is readily available open-access soft...

Zero-shot 3D anomaly detection via online voter mechanism.

Neural networks : the official journal of the International Neural Network Society
3D anomaly detection aims to solve the problem that image anomaly detection is greatly affected by lighting conditions. As commercial confidentiality and personal privacy become increasingly paramount, access to training samples is often restricted. ...

Accuracy of artificial intelligence-based simulation for assessing lung vessels and volume using unenhanced computed tomography.

European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
OBJECTIVES: The advantages of preoperative three-dimensional (3D) image simulations, which require enhanced computed tomography (ECT), for anatomical lung resection are well documented. However, the necessity for contrast agent presents a significant...

MGAug: Multimodal Geometric Augmentation in Latent Spaces of Image Deformations.

Medical image analysis
Geometric transformations have been widely used to augment the size of training images. Existing methods often assume a unimodal distribution of the underlying transformations between images, which limits their power when data with multimodal distrib...

LUNETR: Language-Infused UNETR for precise pancreatic tumor segmentation in 3D medical image.

Neural networks : the official journal of the International Neural Network Society
The identification of early micro-lesions and adjacent blood vessels in CT scans plays a pivotal role in the clinical diagnosis of pancreatic cancer, considering its aggressive nature and high fatality rate. Despite the widespread application of deep...

Geometric deep learning and multiple-instance learning for 3D cell-shape profiling.

Cell systems
The three-dimensional (3D) morphology of cells emerges from complex cellular and environmental interactions, serving as an indicator of cell state and function. In this study, we used deep learning to discover morphology representations and understan...

LW-CTrans: A lightweight hybrid network of CNN and Transformer for 3D medical image segmentation.

Medical image analysis
Recent models based on convolutional neural network (CNN) and Transformer have achieved the promising performance for 3D medical image segmentation. However, these methods cannot segment small targets well even when equipping large parameters. Theref...

AI-driven framework to map the brain metabolome in three dimensions.

Nature metabolism
High-resolution spatial imaging is transforming our understanding of foundational biology. Spatial metabolomics is an emerging field that enables the dissection of the complex metabolic landscape and heterogeneity from a thin tissue section. Currentl...

Robust resolution improvement of 3D UTE-MR angiogram of normal vasculatures using super-resolution convolutional neural network.

Scientific reports
Contrast-enhanced UTE-MRA provides detailed angiographic information but at the cost of prolonged scanning periods, which may impose moving artifacts and affect the promptness of diagnosis and treatment of time-sensitive diseases like stroke. This st...

Stages prediction of Alzheimer's disease with shallow 2D and 3D CNNs from intelligently selected neuroimaging data.

Scientific reports
Detection of Alzheimer's Disease (AD) is critical for successful diagnosis and treatment, involving the common practice of screening for Mild Cognitive Impairment (MCI). However, the progressive nature of AD makes it challenging to identify its causa...