AIMC Topic: Imaging, Three-Dimensional

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Open-source AI-assisted rapid 3D color multimodal image fusion and preoperative augmented reality planning of extracerebral tumors.

Neurosurgical focus
OBJECTIVE: This study aimed to develop an advanced method for preoperative planning and surgical guidance using open-source artificial intelligence (AI)-assisted rapid 3D color multimodal image fusion (MIF) and augmented reality (AR) in extracerebral...

Fully automatic anatomical landmark localization and trajectory planning for navigated external ventricular drain placement.

Neurosurgical focus
OBJECTIVE: The aim of this study was to develop and validate a fully automatic anatomical landmark localization and trajectory planning method for external ventricular drain (EVD) placement using CT or MRI.

How I Do It: Three-Dimensional MR Neurography and Zero Echo Time MRI for Rendering of Peripheral Nerve and Bone.

Radiology
MR neurography sequences provide excellent nerve-to-background soft tissue contrast, whereas a zero echo time (ZTE) MRI sequence provides cortical bone contrast. By demonstrating the spatial relationship between nerves and bones, a combination of ren...

Automated 3D facial smile attractiveness assessment before and after orthognathic surgery using transfer learning: A preliminary study.

Journal of plastic, reconstructive & aesthetic surgery : JPRAS
The aesthetic appearance of the mouth during smiling significantly influences facial attractiveness, thereby, making smile analysis crucial in orthodontics, craniofacial surgery, and cosmetic dentistry. Accurate and quantitative evaluation of facial ...

Improving Imaging Field of View of 3-D Transcranial Rat Brain Super-Resolution With Robotic Registered Compounding and Nonrigid Deformation Correction.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Large field-of-view (FOV) brain imaging with ultrasound has become increasingly achievable with the application of 2-D probes capable of volumetric imaging. However, even in small animals the skull presents a significant barrier and conventional plan...

Transformation trees - Documentation of multimodal image registration.

Computers in biology and medicine
Multimodal image registration plays a key role in creating digital patient models by combining data from different imaging techniques into a single coordinate system. This process often involves multiple sequential and interconnected transformations,...

SegQC: a segmentation network-based framework for multi-metric segmentation quality control and segmentation error detection in volumetric medical images.

Medical image analysis
Quality control (QC) of structures segmentation in volumetric medical images is important for identifying segmentation errors in clinical practice and for facilitating model development by enhancing network performance in semi-supervised and active l...

Error correcting 2D-3D cascaded network for myocardial infarct scar segmentation on late gadolinium enhancement cardiac magnetic resonance images.

Medical image analysis
Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) imaging is considered the in vivo reference standard for assessing infarct size (IS) and microvascular obstruction (MVO) in ST-elevation myocardial infarction (STEMI) patients. Howeve...

Automatic quality control of brain 3D FLAIR MRIs for a clinical data warehouse.

Medical image analysis
Clinical data warehouses, which have arisen over the last decade, bring together the medical data of millions of patients and offer the potential to train and validate machine learning models in real-world scenarios. The quality of MRIs collected in ...

A diffusion-stimulated CT-US registration model with self-supervised learning and synthetic-to-real domain adaptation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
In abdominal interventional procedures, achieving precise registration of 2D ultrasound (US) frames with 3D computed tomography (CT) scans presents a significant challenge. Traditional tracking methods often rely on high-precision sensors, which can ...