AIMC Topic: Radiography

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Lower Extremity Growth according to AI Automated Femorotibial Length Measurement on Slot-Scanning Radiographs in Pediatric Patients.

Radiology
Background Commonly used pediatric lower extremity growth standards are based on small, dated data sets. Artificial intelligence (AI) enables creation of updated growth standards. Purpose To train an AI model using standing slot-scanning radiographs ...

[Deep Learning-Based Key Frame Recognition Algorithm for Adrenal Vascular in X-Ray Imaging].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
Adrenal vein sampling is required for the staging diagnosis of primary aldosteronism, and the frames in which the adrenal veins are presented are called key frames. Currently, the selection of key frames relies on the doctor's visual judgement which ...

[Application of Deep Learning to Diagnose and Classify Adolescent Idiopathic Scoliosis].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
A deep learning-based model for automatic diagnosis and classification of adolescent idiopathic scoliosis has been constructed. This model mainly included key points detection and Cobb angle measurement. 748 full-length standing spinal X-ray images w...

Panoramic imaging errors in machine learning model development: a systematic review.

Dento maxillo facial radiology
OBJECTIVES: To investigate the management of imaging errors from panoramic radiography (PAN) datasets used in the development of machine learning (ML) models.

Environmental Sustainability and AI in Radiology: A Double-Edged Sword.

Radiology
According to the World Health Organization, climate change is the single biggest health threat facing humanity. The global health care system, including medical imaging, must manage the health effects of climate change while at the same time addressi...

Classification of Diagnostic Certainty in Radiology Reports with Deep Learning.

Studies in health technology and informatics
A radiology report is prepared for communicating clinical information about observed abnormal structures and clinically important findings with referring clinicians. However, such observations and findings are often accompanied by ambiguous expressio...

Multiple semantic X-ray medical image retrieval using efficient feature vector extracted by FPN.

Journal of X-ray science and technology
OBJECTIVE: Content-based medical image retrieval (CBMIR) has become an important part of computer-aided diagnostics (CAD) systems. The complex medical semantic information inherent in medical images is the most difficult part to improve the accuracy ...

Clinical Application of Automatic Assessment of Scoliosis Cobb Angle Based on Deep Learning.

Current medical imaging
INTRODUCTION: A recently developed deep-learning-based automatic evaluation model provides reliable and efficient Cobb angle measurements for scoliosis diagnosis. However, few studies have explored its clinical application, and external validation is...

Performance of ChatGPT on the Brazilian Radiology and Diagnostic Imaging and Mammography Board Examinations.

Radiology. Artificial intelligence
This prospective exploratory study conducted from January 2023 through May 2023 evaluated the ability of ChatGPT to answer questions from Brazilian radiology board examinations, exploring how different prompt strategies can influence performance usin...

Strategies for Implementing Machine Learning Algorithms in the Clinical Practice of Radiology.

Radiology
Despite recent advancements in machine learning (ML) applications in health care, there have been few benefits and improvements to clinical medicine in the hospital setting. To facilitate clinical adaptation of methods in ML, this review proposes a s...