AIMC Topic: Radiography

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Impact of imperfection in medical imaging data on deep learning-based segmentation performance: An experimental study using synthesized data.

Medical physics
BACKGROUND: Clinical data used to train deep learning models are often not clean data. They can contain imperfections in both the imaging data and the corresponding segmentations.

Automatic classification of distal radius fracture using a two-stage ensemble deep learning framework.

Physical and engineering sciences in medicine
Distal radius fractures (DRFs) are one of the most common types of wrist fracture and can be subdivided into intra- and extra-articular fractures. Compared with extra-articular DRFs which spare the joint surface, intra-articular DRFs extend to the ar...

Clinical applications of artificial intelligence in radiology.

The British journal of radiology
The rapid growth of medical imaging has placed increasing demands on radiologists. In this scenario, artificial intelligence (AI) has become an attractive partner, one that may complement case interpretation and may aid in various non-interpretive as...

The diagnosis of femoroacetabular impingement can be made on pelvis radiographs using deep learning methods.

Joint diseases and related surgery
OBJECTIVES: The aim of this study was to evaluate diagnostic ability of deep learning models, particularly convolutional neural network models used for image classification, for femoroacetabular impingement (FAI) using hip radiographs.

Experimental validation of computer-vision methods for the successful detection of endodontic treatment obturation and progression from noisy radiographs.

Oral radiology
PURPOSE: (1) To evaluate the effects of denoising and data balancing on deep learning to detect endodontic treatment outcomes from radiographs. (2) To develop and train a deep-learning model and classifier to predict obturation quality from radiomics...

Diagnostic accuracy of a deep learning model using YOLOv5 for detecting developmental dysplasia of the hip on radiography images.

Scientific reports
Developmental dysplasia of the hip (DDH) is a cluster of hip development disorders and one of the most common hip diseases in infants. Hip radiography is a convenient diagnostic tool for DDH, but its diagnostic accuracy is dependent on the interprete...

Accuracy of Information and References Using ChatGPT-3 for Retrieval of Clinical Radiological Information.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
To assess the accuracy of answers provided by ChatGPT-3 when prompted with questions from the daily routine of radiologists and to evaluate the text response when ChatGPT-3 was prompted to provide references for a given answer. ChatGPT-3 (San Franc...

Development and External Validation of an Artificial Intelligence Model for Identifying Radiology Reports Containing Recommendations for Additional Imaging.

AJR. American journal of roentgenology
Reported rates of recommendations for additional imaging (RAIs) in radiology reports are low. Bidirectional encoder representations from transformers (BERT), a deep learning model pretrained to understand language context and ambiguity, has potentia...

Lightweight multi-scale classification of chest radiographs via size-specific batch normalization.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Convolutional neural networks are widely used to detect radiological findings in chest radiographs. Standard architectures are optimized for images of relatively small size (for example, 224 × 224 pixels), which suffices for...