AIMC Topic: Image Processing, Computer-Assisted

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Deep-learning image reconstruction for 80-kVp pancreatic CT protocol: Comparison of image quality and pancreatic ductal adenocarcinoma visibility with hybrid-iterative reconstruction.

European journal of radiology
PURPOSE: To evaluate the image quality and visibility of pancreatic ductal adenocarcinoma (PDAC) in 80-kVp pancreatic CT protocol and compare them between hybrid-iterative reconstruction (IR) and deep-learning image reconstruction (DLIR) algorithms.

The Use of Machine Learning for Image Analysis Artificial Intelligence in Clinical Microbiology.

Journal of clinical microbiology
The growing transition to digital microbiology in clinical laboratories creates the opportunity to interpret images using software. Software analysis tools can be designed to use human-curated knowledge and expert rules, but more novel artificial int...

Human examination and artificial intelligence in cephalometric landmark detection-is AI ready to take over?

Dento maxillo facial radiology
OBJECTIVES: To compare the precision of two cephalometric landmark identification methods, namely a computer-assisted human examination software and an artificial intelligence program, based on South African data.

Detecting dental caries on oral photographs using artificial intelligence: A systematic review.

Oral diseases
OBJECTIVES: This systematic review aimed at evaluating the performance of artificial intelligence (AI) models in detecting dental caries on oral photographs.

Deep Learning-Based Image Noise Quantification Framework for Computed Tomography.

Journal of computer assisted tomography
OBJECTIVE: Noise quantification is fundamental to computed tomography (CT) image quality assessment and protocol optimization. This study proposes a deep learning-based framework, Single-scan Image Local Variance EstimatoR (SILVER), for estimating th...

Deep Learning Reconstruction Plus Single-Energy Metal Artifact Reduction for Supra Hyoid Neck CT in Patients With Dental Metals.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
We investigated the effect of deep learning reconstruction (DLR) plus single-energy metal artifact reduction (SEMAR) on neck CT in patients with dental metals, comparing it with DLR and with hybrid iterative reconstruction (Hybrid IR)-SEMAR. In thi...

Deep learning-based combination of [18F]-FDG PET and CT images for producing pulmonary perfusion image.

Medical physics
BACKGROUND: The main application of [18F] FDG-PET ( FDG-PET) and CT images in oncology is tumor identification and quantification. Combining PET and CT images to mine pulmonary perfusion information for functional lung avoidance radiation therapy (FL...

Clinical applications of graph neural networks in computational histopathology: A review.

Computers in biology and medicine
Pathological examination is the optimal approach for diagnosing cancer, and with the advancement of digital imaging technologies, it has spurred the emergence of computational histopathology. The objective of computational histopathology is to assist...

A continuation method for image registration based on dynamic adaptive kernel.

Neural networks : the official journal of the International Neural Network Society
Image registration is a fundamental problem in computer vision and robotics. Recently, learning-based image registration methods have made great progress. However, these methods are sensitive to abnormal transformation and have insufficient robustnes...

Two-Stage Self-Supervised Cycle-Consistency Transformer Network for Reducing Slice Gap in MR Images.

IEEE journal of biomedical and health informatics
Magnetic resonance (MR) images are usually acquired with large slice gap in clinical practice, i.e., low resolution (LR) along the through-plane direction. It is feasible to reduce the slice gap and reconstruct high-resolution (HR) images with the de...