AIMC Topic: Imaging, Three-Dimensional

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Novel robotic technology for the rapid intraoperative manufacture of patient-specific instrumentation allowing for improved glenoid component accuracy in shoulder arthroplasty: a cadaveric study.

Journal of shoulder and elbow surgery
BACKGROUND: Accurate prosthesis placement in arthroplasty is an important factor in the long-term success of these interventions. Many types of guidance technology have been described to date often suffering from high costs, complex theater integrati...

Breath-hold 3D magnetic resonance cholangiopancreatography at 1.5 T using a deep learning-based noise-reduction approach: Comparison with the conventional respiratory-triggered technique.

European journal of radiology
OBJECTIVES: To assess the image quality of conventional respiratory-triggered 3-dimentional (3D) magnetic resonance cholangiopancreatography (Resp-MRCP) and breath-hold 3D MRCP (BH-MRCP) with and without denoising procedure using deep learning-based ...

Classification of Alzheimer's Disease Using Gaussian-Based Bayesian Parameter Optimization for Deep Convolutional LSTM Network.

Computational and mathematical methods in medicine
Alzheimer's disease (AD) is one of the most important causes of mortality in elderly people, and it is often challenging to use traditional manual procedures when diagnosing a disease in the early stages. The successful implementation of machine lear...

Few-Shot Learning by a Cascaded Framework With Shape-Constrained Pseudo Label Assessment for Whole Heart Segmentation.

IEEE transactions on medical imaging
Automatic and accurate 3D cardiac image segmentation plays a crucial role in cardiac disease diagnosis and treatment. Even though CNN based techniques have achieved great success in medical image segmentation, the expensive annotation, large memory c...

3D MRI Models of the Musculoskeletal System.

Seminars in musculoskeletal radiology
Computed tomography (CT) is most commonly used to produce three-dimensional (3D) models for evaluating bone and joint morphology in clinical practice. However, 3D models created from magnetic resonance imaging (MRI) data can be equally effective for ...

Deep Learning-Based Three-Dimensional Oral Conical Beam Computed Tomography for Diagnosis.

Journal of healthcare engineering
In order to deeply study oral three-dimensional cone beam computed tomography (CBCT), the diagnosis of oral and facial surgical diseases based on deep learning was studied. The utility model related to a deep learning-based classification algorithm f...

Peak learning of mass spectrometry imaging data using artificial neural networks.

Nature communications
Mass spectrometry imaging (MSI) is an emerging technology that holds potential for improving, biomarker discovery, metabolomics research, pharmaceutical applications and clinical diagnosis. Despite many solutions being developed, the large data size ...

An Unsupervised Learning-Based Multi-Organ Registration Method for 3D Abdominal CT Images.

Sensors (Basel, Switzerland)
Medical image registration is an essential technique to achieve spatial consistency geometric positions of different medical images obtained from single- or multi-sensor, such as computed tomography (CT), magnetic resonance (MR), and ultrasound (US) ...

Integration of imaging modalities in digital dental workflows - possibilities, limitations, and potential future developments.

Dento maxillo facial radiology
The digital workflow process follows different steps for all dental specialties. However, the main ingredient for the diagnosis, treatment planning and follow-up workflow recipes is the imaging chain. The steps in the imaging chain usually include al...