AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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Artificial Intelligence for Identification of Images with Active Bleeding in Mesenteric and Celiac Arteries Angiography.
Cardiovascular and interventional radiology
Mar 26, 2024
PURPOSE: The purpose of this study is to evaluate the efficacy of an artificial intelligence (AI) model designed to identify active bleeding in digital subtraction angiography images for upper gastrointestinal bleeding.
Artificial Intelligence
Mesenteric Arteries
Embolization, Therapeutic
Algorithms
Male
Female
Humans
Celiac Artery
Retrospective Studies
Middle Aged
Aged
Gastrointestinal Hemorrhage
Radiographic Image Interpretation, Computer-Assisted
Adult
Angiography, Digital Subtraction
Sensitivity and Specificity
Robust deep learning from incomplete annotation for accurate lung nodule detection.
Computers in biology and medicine
Mar 26, 2024
Deep learning plays a significant role in the detection of pulmonary nodules in low-dose computed tomography (LDCT) scans, contributing to the diagnosis and treatment of lung cancer. Nevertheless, its effectiveness often relies on the availability of...
Enhancing Lung Nodule Classification: A Novel CViEBi-CBGWO Approach with Integrated Image Preprocessing.
Journal of imaging informatics in medicine
Mar 25, 2024
Cancer detection and accurate classification pose significant challenges for medical professionals, as it is described as a lethal illness. Diagnosing the malignant lung nodules in its initial stage significantly enhances the recovery and survival ra...
Deep learning reconstruction for high-resolution computed tomography images of the temporal bone: comparison with hybrid iterative reconstruction.
Neuroradiology
Mar 22, 2024
PURPOSE: We investigated whether the quality of high-resolution computed tomography (CT) images of the temporal bone improves with deep learning reconstruction (DLR) compared with hybrid iterative reconstruction (HIR).
Exploring the Low-Dose Limit for Focal Hepatic Lesion Detection with a Deep Learning-Based CT Reconstruction Algorithm: A Simulation Study on Patient Images.
Journal of imaging informatics in medicine
Mar 19, 2024
This study aims to investigate the maximum achievable dose reduction for applying a new deep learning-based reconstruction algorithm, namely the artificial intelligence iterative reconstruction (AIIR), in computed tomography (CT) for hepatic lesion d...
Artificial intelligence for caries detection: a novel diagnostic tool using deep learning algorithms.
Oral radiology
Mar 18, 2024
OBJECTIVES: The aim of this study was to develop an assessment tool for automatic detection of dental caries in periapical radiographs using convolutional neural network (CNN) architecture.
Improved overall image quality in low-dose dual-energy computed tomography enterography using deep-learning image reconstruction.
Abdominal radiology (New York)
Mar 14, 2024
OBJECTIVE: To demonstrate the clinical advantages of a deep-learning image reconstruction (DLIR) in low-dose dual-energy computed tomography enterography (DECTE) by comparing images with standard-dose adaptive iterative reconstruction-Veo (ASIR-V) im...
Automatic estimation of hallux valgus angle using deep neural network with axis-based annotation.
Skeletal radiology
Mar 13, 2024
OBJECTIVES: We developed the deep neural network (DNN) model to automatically measure hallux valgus angle (HVA) and intermetatarsal angle (IMA) on foot radiographs. The objective is to assess the accuracy of the model by comparing to the manual measu...
Adaptive Machine Learning Approach for Importance Evaluation of Multimodal Breast Cancer Radiomic Features.
Journal of imaging informatics in medicine
Mar 13, 2024
Breast cancer holds the highest diagnosis rate among female tumors and is the leading cause of death among women. Quantitative analysis of radiological images shows the potential to address several medical challenges, including the early detection an...
Detection of urinary tract stones on submillisievert abdominopelvic CT imaging with deep-learning image reconstruction algorithm (DLIR).
Abdominal radiology (New York)
Mar 12, 2024
PURPOSE: Urolithiasis is a chronic condition that leads to repeated CT scans throughout the patient's life. The goal was to assess the diagnostic performance and image quality of submillisievert abdominopelvic computed tomography (CT) using deep lear...
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