AIMC Topic: Bone and Bones

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Extended-wavelength diffuse reflectance spectroscopy dataset of animal tissues for bone-related biomedical applications.

Scientific data
Diffuse reflectance spectroscopy (DRS) has been extensively studied in both preclinical and clinical settings for multiple applications, notably as a minimally invasive diagnostic tool for tissue identification and disease delineation. In this study,...

A convolutional neural network-based method for the generation of super-resolution 3D models from clinical CT images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The accurate evaluation of bone mechanical properties is essential for predicting fracture risk based on clinical computed tomography (CT) images. However, blurring and noise in clinical CT images can compromise the accuracy...

Deep learning to overcome Zernike phase-contrast nanoCT artifacts for automated micro-nano porosity segmentation in bone.

Journal of synchrotron radiation
Bone material contains a hierarchical network of micro- and nano-cavities and channels, known as the lacuna-canalicular network (LCN), that is thought to play an important role in mechanobiology and turnover. The LCN comprises micrometer-sized lacuna...

Automatic craniomaxillofacial landmarks detection in CT images of individuals with dentomaxillofacial deformities by a two-stage deep learning model.

BMC oral health
BACKGROUND: Accurate cephalometric analysis plays a vital role in the diagnosis and subsequent surgical planning in orthognathic and orthodontics treatment. However, manual digitization of anatomical landmarks in computed tomography (CT) is subject t...

Prediction and related genes of cancer distant metastasis based on deep learning.

Computers in biology and medicine
Cancer metastasis is one of the main causes of cancer progression and difficulty in treatment. Genes play a key role in the process of cancer metastasis, as they can influence tumor cell invasiveness, migration ability and fitness. At the same time, ...

The CNN model aided the study of the clinical value hidden in the implant images.

Journal of applied clinical medical physics
PURPOSE: This article aims to construct a new method to evaluate radiographic image identification results based on artificial intelligence, which can complement the limited vision of researchers when studying the effect of various factors on clinica...

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...