AIMC Topic: Bone and Bones

Clear Filters Showing 41 to 50 of 147 articles

Hybrid artificial muscle: enhanced actuation and load-bearing performance an origami metamaterial endoskeleton.

Materials horizons
Owing to their compliance, soft robots demonstrate enhanced compatibility with humans and the environment compared with traditional rigid robots. However, ensuring the working effectiveness of artificial muscles that actuate soft robots in confined s...

Decomposition of musculoskeletal structures from radiographs using an improved CycleGAN framework.

Scientific reports
This paper presents methods of decomposition of musculoskeletal structures from radiographs into multiple individual muscle and bone structures. While existing solutions require dual-energy scan for the training dataset and are mainly applied to stru...

Artificial intelligence-aided lytic spinal bone metastasis classification on CT scans.

International journal of computer assisted radiology and surgery
PURPOSE: Spinal bone metastases directly affect quality of life, and patients with lytic-dominant lesions are at high risk for neurological symptoms and fractures. To detect and classify lytic spinal bone metastasis using routine computed tomography ...

Artificial intelligence-based analysis of whole-body bone scintigraphy: The quest for the optimal deep learning algorithm and comparison with human observer performance.

Zeitschrift fur medizinische Physik
PURPOSE: Whole-body bone scintigraphy (WBS) is one of the most widely used modalities in diagnosing malignant bone diseases during the early stages. However, the procedure is time-consuming and requires vigour and experience. Moreover, interpretation...

A real-time automated bone age assessment system based on the RUS-CHN method.

Frontiers in endocrinology
BACKGROUND: Bone age is the age of skeletal development and is a direct indicator of physical growth and development in children. Most bone age assessment (BAA) systems use direct regression with the entire hand bone map or first segmenting the regio...

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...

Advances in materials-based therapeutic strategies against osteoporosis.

Biomaterials
Osteoporosis is caused by the disruption in homeostasis between bone formation and bone resorption. Conventional management of osteoporosis involves systematic drug administration and hormonal therapy. These treatment strategies have limited curative...

Self-Supervised Learning for Non-Rigid Registration Between Near-Isometric 3D Surfaces in Medical Imaging.

IEEE transactions on medical imaging
Non-rigid registration between 3D surfaces is an important but notorious problem in medical imaging, because finding correspondences between non-isometric instances is mathematically non-trivial. We propose a novel self-supervised method to learn sha...

Original research: utilization of a convolutional neural network for automated detection of lytic spinal lesions on body CTs.

Skeletal radiology
OBJECTIVE: To develop, train, and test a convolutional neural network (CNN) for detection of spinal lytic lesions in chest, abdomen, and pelvis CT scans.

Prediction of Bone Healing around Dental Implants in Various Boundary Conditions by Deep Learning Network.

International journal of molecular sciences
Tissue differentiation varies based on patients' conditions, such as occlusal force and bone properties. Thus, the design of the implants needs to take these conditions into account to improve osseointegration. However, the efficiency of the design p...