AIMC Topic: Bone and Bones

Clear Filters Showing 31 to 40 of 147 articles

Automatic Skeleton Segmentation in CT Images Based on U-Net.

Journal of imaging informatics in medicine
Bone metastasis, emerging oncological therapies, and osteoporosis represent some of the distinct clinical contexts which can result in morphological alterations in bone structure. The visual assessment of these changes through anatomical images is co...

Fast SPECT/CT planar bone imaging enabled by deep learning enhancement.

Medical physics
BACKGROUND: The application of deep learning methods in rapid bone scintigraphy is increasingly promising for minimizing the duration of SPECT examinations. Recent works showed several deep learning models based on simulated data for the synthesis of...

Registration of multimodal bone images based on edge similarity metaheuristic.

Computers in biology and medicine
OBJECTIVE: Blurry medical images affect the accuracy and efficiency of multimodal image registration, whose existing methods require further improvement.

An explainable machine learning-based probabilistic framework for the design of scaffolds in bone tissue engineering.

Biomechanics and modeling in mechanobiology
Recently, 3D-printed biodegradable scaffolds have shown great potential for bone repair in critical-size fractures. The differentiation of the cells on a scaffold is impacted among other factors by the surface deformation of the scaffold due to mecha...

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...