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Bone Density

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Deep-learning image reconstruction for image quality evaluation and accurate bone mineral density measurement on quantitative CT: A phantom-patient study.

Frontiers in endocrinology
BACKGROUND AND PURPOSE: To investigate the image quality and accurate bone mineral density (BMD) on quantitative CT (QCT) for osteoporosis screening by deep-learning image reconstruction (DLIR) based on a multi-phantom and patient study.

Identification of osteoporosis using ensemble deep learning model with panoramic radiographs and clinical covariates.

Scientific reports
Osteoporosis is becoming a global health issue due to increased life expectancy. However, it is difficult to detect in its early stages owing to a lack of discernible symptoms. Hence, screening for osteoporosis with widely used dental panoramic radio...

Cardiovascular Disease Diagnosis from DXA Scan and Retinal Images Using Deep Learning.

Sensors (Basel, Switzerland)
Cardiovascular diseases (CVD) are the leading cause of death worldwide. People affected by CVDs may go undiagnosed until the occurrence of a serious heart failure event such as stroke, heart attack, and myocardial infraction. In Qatar, there is a lac...

Construction of a new automatic grading system for jaw bone mineral density level based on deep learning using cone beam computed tomography.

Scientific reports
To develop and verify an automatic classification method using artificial intelligence deep learning to determine the bone mineral density level of the implant site in oral implant surgery from radiographic data obtained from cone beam computed tomog...

Development of a Spine X-Ray-Based Fracture Prediction Model Using a Deep Learning Algorithm.

Endocrinology and metabolism (Seoul, Korea)
BACKGRUOUND: Since image-based fracture prediction models using deep learning are lacking, we aimed to develop an X-ray-based fracture prediction model using deep learning with longitudinal data.

Osteoporosis screening support system from panoramic radiographs using deep learning by convolutional neural network.

Dento maxillo facial radiology
OBJECTIVES: This study was performed to develop computer-aided screening systems that could predict osteoporosis. The systems were constructed using panoramic radiographs of women aged ≥ 50 years through three types of deep convolutional neural netwo...

Automated, calibration-free quantification of cortical bone porosity and geometry in postmenopausal osteoporosis from ultrashort echo time MRI and deep learning.

Bone
BACKGROUND: Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful information about bone quality that is independent of bone mineral density (BMD). Ultrashort echo time (UTE) MRI techniques of measuring cortical bone...

A semi-autonomous robot control based on bone layer transition detection for a safe pedicle tapping.

International journal of computer assisted radiology and surgery
PURPOSE: Automatic robotic platforms for robot-aided spinal surgery are mostly employed for drilling the pedicle screw path and do not adapt the tool rotational speed depending on the variation of the bone density. This feature is highly desirable in...

Feasibility of Bone Mineral Density and Bone Microarchitecture Assessment Using Deep Learning With a Convolutional Neural Network.

Journal of computer assisted tomography
OBJECTIVES: We evaluated the feasibility of using deep learning with a convolutional neural network for predicting bone mineral density (BMD) and bone microarchitecture from conventional computed tomography (CT) images acquired by multivendor scanner...

Deep-Learning-Based Detection of Vertebral Fracture and Osteoporosis Using Lateral Spine X-Ray Radiography.

Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
Osteoporosis and vertebral fractures (VFs) remain underdiagnosed. The addition of deep learning methods to lateral spine radiography (a simple, widely available, low-cost test) can potentially solve this problem. In this study, we develop deep learni...