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Bone and Bones

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Bone collision detection method for robot assisted fracture reduction based on force curve slope.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The application of robot technology in fracture reduction ensures the minimal invasiveness and accurate operation process. Most of the existing robot assisted fracture reduction systems don't have the function of bone collis...

Deep learning approach to assess damage mechanics of bone tissue.

Journal of the mechanical behavior of biomedical materials
Machine learning methods have the potential to transform imaging techniques and analysis for healthcare applications with automation, making diagnostics and treatment more accurate and efficient, as well as to provide mechanistic insights into tissue...

dSPIC: a deep SPECT image classification network for automated multi-disease, multi-lesion diagnosis.

BMC medical imaging
BACKGROUND: Functional imaging especially the SPECT bone scintigraphy has been accepted as the effective clinical tool for diagnosis, treatment, evaluation, and prevention of various diseases including metastasis. However, SPECT imaging is brightly c...

Deep learning methods for automatic segmentation of lower leg muscles and bones from MRI scans of children with and without cerebral palsy.

NMR in biomedicine
Cerebral palsy is a neurological condition that is known to affect muscle growth. Detailed investigations of muscle growth require segmentation of muscles from MRI scans, which is typically done manually. In this study, we evaluated the performance o...

Multitask Deep Learning for Segmentation and Classification of Primary Bone Tumors on Radiographs.

Radiology
Background An artificial intelligence model that assesses primary bone tumors on radiographs may assist in the diagnostic workflow. Purpose To develop a multitask deep learning (DL) model for simultaneous bounding box placement, segmentation, and cla...

Automatic identification of suspicious bone metastatic lesions in bone scintigraphy using convolutional neural network.

BMC medical imaging
BACKGROUND: We aimed to construct an artificial intelligence (AI) guided identification of suspicious bone metastatic lesions from the whole-body bone scintigraphy (WBS) images by convolutional neural networks (CNNs).

Generation of Vertebra Micro-CT-like Image from MDCT: A Deep-Learning-Based Image Enhancement Approach.

Tomography (Ann Arbor, Mich.)
This paper proposes a deep-learning-based image enhancement approach that can generate high-resolution micro-CT-like images from multidetector computed tomography (MDCT). A total of 12,500 MDCT and micro-CT image pairs were obtained from 25 vertebral...

Biohybrid Variable-Stiffness Soft Actuators that Self-Create Bone.

Advanced materials (Deerfield Beach, Fla.)
Inspired by the dynamic process of initial bone development, in which a soft tissue turns into a solid load-bearing structure, the fabrication, optimization, and characterization of bioinduced variable-stiffness actuators that can morph in various sh...

A CT Image-Based Virtual Sensing Method to Estimate Bone Drilling Force for Surgical Robots.

IEEE transactions on bio-medical engineering
OBJECTIVE: Current surgical robots face challenges to understand preoperative images like human surgeons, which hindering robots from making full use of preoperative information to operate stably and efficiently. We offer a method to estimate drillin...

Bone segmentation in contrast enhanced whole-body computed tomography.

Biomedical physics & engineering express
Segmentation of bone regions allows for enhanced diagnostics, disease characterisation and treatment monitoring in CT imaging. In contrast enhanced whole-body scans accurate automatic segmentation is particularly difficult as low dose whole body prot...