AIMC Topic: Radiography
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Deep learning can detect elbow disease in dogs screened for elbow dysplasia.
Veterinary radiology & ultrasound : the official journal of the American College of Veterinary Radiology and the International Veterinary Radiology Association
Jan 1, 2025
Medical image analysis based on deep learning is a rapidly advancing field in veterinary diagnostics. The aim of this retrospective diagnostic accuracy study was to develop and assess a convolutional neural network (CNN, EfficientNet) to evaluate elb...
Generative AI in orthopedics: an explainable deep few-shot image augmentation pipeline for plain knee radiographs and Kellgren-Lawrence grading.
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2024
OBJECTIVES: Recently, deep learning medical image analysis in orthopedics has become highly active. However, progress has been restricted by the absence of large-scale and standardized ground-truth images. To the best of our knowledge, this study is ...
[Study on automatic and rapid diagnosis of distal radius fracture by X-ray].
Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Aug 25, 2024
This article aims to combine deep learning with image analysis technology and propose an effective classification method for distal radius fracture types. Firstly, an extended U-Net three-layer cascaded segmentation network was used to accurately seg...
Interobserver Agreement and Performance of Concurrent AI Assistance for Radiographic Evaluation of Knee Osteoarthritis.
Radiology
Jul 1, 2024
Background Due to conflicting findings in the literature, there are concerns about a lack of objectivity in grading knee osteoarthritis (KOA) on radiographs. Purpose To examine how artificial intelligence (AI) assistance affects the performance and i...
Detection of Cervical Foraminal Stenosis from Oblique Radiograph Using Convolutional Neural Network Algorithm.
Yonsei medical journal
Jul 1, 2024
PURPOSE: This study was conducted to develop a convolutional neural network (CNN) algorithm that can diagnose cervical foraminal stenosis using oblique radiographs and evaluate its accuracy.
Automatic diagnosis of pediatric supracondylar humerus fractures using radiomics-based machine learning.
Medicine
Jun 7, 2024
The aim of this study was to construct a classification model for the automatic diagnosis of pediatric supracondylar humerus fractures using radiomics-based machine learning. We retrospectively collected elbow joint Radiographs of children aged 3 to ...
Role of artificial intelligence (Google bard) in morphological, histopathological, and radiological image identifications: Objective Structured Practical Examination (OSPE) type-based performance.
Saudi medical journal
May 1, 2024
OBJECTIVES: To evaluate the role of artificial intelligence (Google Bard) in figures, scans, and image identifications and interpretations in medical education and healthcare sciences through an Objective Structured Practical Examination (OSPE) type ...
Invited Commentary: The Double-edged Sword of Bias in Medical Imaging Artificial Intelligence.
Radiographics : a review publication of the Radiological Society of North America, Inc
May 1, 2024
Evaluating the Robustness of a Deep Learning Bone Age Algorithm to Clinical Image Variation Using Computational Stress Testing.
Radiology. Artificial intelligence
May 1, 2024
Purpose To evaluate the robustness of an award-winning bone age deep learning (DL) model to extensive variations in image appearance. Materials and Methods In December 2021, the DL bone age model that won the 2017 RSNA Pediatric Bone Age Challenge wa...
AI-assisted Analysis to Facilitate Detection of Humeral Lesions on Chest Radiographs.
Radiology. Artificial intelligence
May 1, 2024
Purpose To develop an artificial intelligence (AI) system for humeral tumor detection on chest radiographs (CRs) and evaluate the impact on reader performance. Materials and Methods In this retrospective study, 14 709 CRs (January 2000 to December 20...
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