相关论文: Automatic detection and diagnosis of sacroiliitis …
Wrist pathologies, {particularly fractures common among children and adolescents}, present a critical diagnostic challenge. While X-ray imaging remains a prevalent diagnostic tool, the increasing misinterpretation rates highlight the need…
This paper aims to detect the potential injury risk of the anterior cruciate ligament (ACL) by proposing an ACL potential injury risk assessment algorithm based on key points of the human body detected using computer vision technology. To…
Standardized body region labelling of individual images provides data that can improve human and computer use of medical images. A CNN-based classifier was developed to identify body regions in CT and MRI. 17 CT (18 MRI) body regions…
Medical image analysis tasks often focus on regions or structures located in a particular location within the patient's body. Often large parts of the image may not be of interest for the image analysis task. When using deep-learning based…
Purpose: Develop AI-based automated CT image analysis tools for detection, quantification, and tracking of Coronavirus; demonstrate they can differentiate coronavirus patients from non-patients. Materials and Methods: Multiple international…
To decrease patient waiting time for diagnosis of the Coronary Artery Disease, automatic methods are applied to identify its severity using Coronary Computed Tomography Angiography scans or extracted Multiplanar Reconstruction (MPR) images,…
Several pathologies can alter the way people walk, i.e. their gait. Gait analysis can therefore be used to detect impairments and help diagnose illnesses and assess patient recovery. Using vision-based systems, diagnoses could be done at…
A large number of different lesions and pathologies can affect the human digestive system, resulting in life-threatening situations. Early detection plays a relevant role in the successful treatment and the increase of current survival…
Motion artifacts can compromise the diagnostic value of computed tomography (CT) images. Motion correction approaches require a per-scan estimation of patient-specific motion patterns. In this work, we train a score-based model to act as a…
Despite coronary artery calcium scoring being considered a largely solved problem within the realm of medical artificial intelligence, this paper argues that significant improvements can still be made. By shifting the focus from pathology…
Artificial intelligence is set to be deployed in operating rooms to improve surgical care. This early-stage clinical evaluation shows the feasibility of concurrently attaining real-time, high-quality predictions from several deep neural…
Artificial intelligence may assist healthcare systems in meeting increasing demand for pathology services while maintaining diagnostic quality and reducing turnaround time and costs. We aimed to investigate the performance of an…
Ultrasound imaging has been widely used in clinical examinations owing to the advantages of being portable, real-time, and radiation-free. Considering the potential of extensive deployment of autonomous examination systems in hospitals,…
Despite high global prevalence of hepatic steatosis, no automated diagnostics demonstrated generalizability in detecting steatosis on multiple international datasets. Traditionally, hepatic steatosis detection relies on clinicians selecting…
Introduction: Bone health disorders like osteoarthritis and osteoporosis pose major global health challenges, often leading to delayed diagnoses due to limited diagnostic tools. This study presents an AI-powered system that analyzes knee…
The chest X-Ray (CXR) is the one of the most common clinical exam used to diagnose thoracic diseases and abnormalities. The volume of CXR scans generated daily in hospitals is huge. Therefore, an automated diagnosis system able to save the…
The high prevalence of spinal stenosis results in a large volume of MRI imaging, yet interpretation can be time-consuming with high inter-reader variability even among the most specialized radiologists. In this paper, we develop an…
How to accurately classify and diagnose whether an individual has Coronary Stenosis (CS) without invasive physical examination? This problem has not been solved satisfactorily. To this end, the four machine learning (ML) algorithms, i.e.,…
The use of automatic systems in the analysis of medical images has proven to be very useful to radiologists, especially in the framework of screening programs, in which radiologists make their first diagnosis on the basis of images only,…
Traumatic brain injuries could cause intracranial hemorrhage (ICH). ICH could lead to disability or death if it is not accurately diagnosed and treated in a time-sensitive procedure. The current clinical protocol to diagnose ICH is…