AIMC Topic: X-Ray Microtomography

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Automated 3D segmentation of human vagus nerve fascicles and epineurium from micro-computed tomography images using anatomy-aware neural networks.

Journal of neural engineering
Objective.Precise segmentation and quantification of nerve morphology from imaging data are critical for designing effective and selective peripheral nerve stimulation (PNS) therapies. However, prior studies on nerve morphology segmentation suffer fr...

Deep learning-based detection of murine congenital heart defects from µCT scans.

Communications biology
Micro-computed tomography (μCT) provides 3D images of congenital heart defects (CHD) in mice. However, diagnosing CHD from μCT scans is time-consuming and requires clinical expertise. Here, we present a deep learning approach to automatically segment...

Accuracy of deep learning-based AI models for early caries lesion detection: the influence of annotation quality and reference choice.

Clinical oral investigations
OBJECTIVES: The objective of this study is to assess how different annotation methods used during AI model training affect the accuracy of early caries lesion detection, and how the choice of the evaluation reference standard leads to significant dif...

A deep learning-based framework for standardized analysis of trabecular bone compartments from micro-CT imaging data in the mouse tibia.

Scientific reports
Understanding bone remodeling and disease progression is crucial in preclinical skeletal research, particularly for assessing pharmacological and mechanical interventions in the long bones of murine models. High-resolution micro-computed tomography (...

AI-based modality-agnostic classification system for vascular calcifications.

Scientific reports
The importance of vascular calcification in major adverse cardiovascular events such as heart attacks or strokes has been established. However, calcifications have heterogeneous phenotypes, and their influence on diseased tissue stability remains poo...

2D-3D deformable image registration of histology slide and micro-CT with DISA-based initialization.

Scientific reports
Recent developments in the registration of histology and micro-computed tomography (µCT) have broadened the perspective of pathological applications such as virtual histology based on µCT. This topic remains challenging because of the low image quali...

Ensemble methods and partially-supervised learning for accurate and robust automatic murine organ segmentation.

Scientific reports
Delineation of multiple organs in murine µCT images is crucial for preclinical studies but requires manual volumetric segmentation, a tedious and time-consuming process prone to inter-observer variability. Automatic deep learning-based segmentation c...

Volumetric atlas of the rat inner ear from microCT and iDISCO+ cleared temporal bones.

PeerJ
BACKGROUND: Volumetric atlases are an invaluable tool in neuroscience and otolaryngology, greatly aiding experiment planning and surgical interventions, as well as the interpretation of experimental and clinical data. The rat is a major animal model ...

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 ...

Assessing the cardioprotective effects of exercise in APOE mouse models using deep learning and photon-counting micro-CT.

PloS one
BACKGROUND: The allelic variations of the apolipoprotein E (APOE) gene play a critical role in regulating lipid metabolism and significantly impact cardiovascular disease risk (CVD). This study aimed to evaluate the impact of exercise on cardiac stru...