AIMC Topic: Imaging, Three-Dimensional

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Model-Based Convolution Neural Network for 3D Near-Infrared Spectral Tomography.

IEEE transactions on medical imaging
Near-infrared spectral tomography (NIRST) is a non-invasive imaging technique that provides functional information about biological tissues. Due to diffuse light propagation in tissue and limited boundary measurements, NIRST image reconstruction pres...

Boosting Convolution With Efficient MLP-Permutation for Volumetric Medical Image Segmentation.

IEEE transactions on medical imaging
Recently, the advent of Vision Transformer (ViT) has brought substantial advancements in 3D benchmarks, particularly in 3D volumetric medical image segmentation (Vol-MedSeg). Concurrently, multi-layer perceptron (MLP) network has regained popularity ...

High-Resolution Maps of Left Atrial Displacements and Strains Estimated With 3D Cine MRI Using Online Learning Neural Networks.

IEEE transactions on medical imaging
The functional analysis of the left atrium (LA) is important for evaluating cardiac health and understanding diseases like atrial fibrillation. Cine MRI is ideally placed for the detailed 3D characterization of LA motion and deformation but is lackin...

Role Exchange-Based Self-Training Semi-Supervision Framework for Complex Medical Image Segmentation.

IEEE transactions on neural networks and learning systems
Segmentation of complex medical images such as vascular network and pulmonary tracheal network requires segmentation of many tiny targets on each tomographic section of the 3-D medical image volume. Although semantic segmentation of medical images ba...

Computer-aided diagnosis tool utilizing a deep learning model for preoperative T-staging of rectal cancer based on three-dimensional endorectal ultrasound.

Abdominal radiology (New York)
BACKGROUND: The prognosis and treatment outcomes for patients with rectal cancer are critically dependent on an accurate and comprehensive preoperative evaluation.Three-dimensional endorectal ultrasound (3D-ERUS) has demonstrated high accuracy in the...

3D tooth identification for forensic dentistry using deep learning.

BMC oral health
The classification of intraoral teeth structures is a critical component in modern dental analysis and forensic dentistry. Traditional methods, relying on 2D imaging, often suffer from limitations in accuracy and comprehensiveness due to the complex ...

Digital Innovations in Orthognathic Surgery: A Systematic Review of Virtual Surgical Planning, Digital Transfer, and Conventional Model Surgery.

Orthodontics & craniofacial research
OBJECTIVES: Orthognathic surgery has evolved due to the use of virtual surgical planning (VSP) and digital model surgery, which are technological advancements replacing conventional approaches with accurate personalised digital models made from compu...

On-farm 3D images of beef cattle for the prediction of carcass classification traits and cold carcass weight.

Animal : an international journal of animal bioscience
For beef cattle, subjective methods tend to be used on-farm for assessing readiness for slaughter. This means that the target classification grades cannot be accurately estimated, leading to over- and under-finished animals being sent to slaughter. T...

Enhancing Patient Acceptance of Robotic Ultrasound through Conversational Virtual Agent and Immersive Visualizations.

IEEE transactions on visualization and computer graphics
Robotic ultrasound systems have the potential to improve medical diagnostics, but patient acceptance remains a key challenge. To address this, we propose a novel system that combines an AI-based virtual agent, powered by a large language model (LLM),...

A high-throughput framework for predicting three-dimensional structural-mechanical relationships of human cranial bones using a deep learning-based method.

Journal of the mechanical behavior of biomedical materials
Cranial bone injuries significantly impact human health, potentially leading to death or permanent disability, and mechanical responses are crucial predictors of cranial damage. Predicting mechanical responses through medical imaging is an efficient ...