AIMC Topic: Tomography, X-Ray Computed

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Self-Supervised Optimization of RF Data Coherence for Improving Breast Reflection UCT Reconstruction.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
The reflection ultrasound computed tomography (UCT) is gaining prominence as an essential instrument for breast cancer screening. However, reflection UCT quality is often compromised by the variability in sound speed across breast tissue. Traditional...

Impact of Deep Learning-Based Image Conversion on Fully Automated Coronary Artery Calcium Scoring Using Thin-Slice, Sharp-Kernel, Non-Gated, Low-Dose Chest CT Scans: A Multi-Center Study.

Korean journal of radiology
OBJECTIVE: To evaluate the impact of deep learning-based image conversion on the accuracy of automated coronary artery calcium quantification using thin-slice, sharp-kernel, non-gated, low-dose chest computed tomography (LDCT) images collected from m...

Sex-estimation method for three-dimensional shapes of the skull and skull parts using machine learning.

Forensic science international
Sex estimation is an indispensable test for identifying skeletal remains in the field of forensic anthropology. We developed a novel sex-estimation method for skulls and several parts of the skull using machine learning. A total of 240 skull shapes w...

A review: Lightweight architecture model in deep learning approach for lung disease identification.

Computers in biology and medicine
As one of the leading causes of death worldwide, early detection of lung disease is a very important step to improve the effectiveness of treatment. By using medical image data, such as X-ray or CT-scan, classification of lung disease can be done. De...

Automated three-dimensional body composition analysis identifies visceral adipose tissue radiodensity as a predictor of mortality and recurrence in colorectal cancer.

Clinical nutrition (Edinburgh, Scotland)
BACKGROUND: Artificial intelligence enables automated three-dimensional (3D) volumetric body composition (BC) analysis from computed tomography (CT), opposed to single third lumbar vertebra (L3) slices alone. This study aimed to identify relationship...

Accelerating Diffusion: Task-Optimized latent diffusion models for rapid CT denoising.

Computers in biology and medicine
Computed tomography (CT) systems are indispensable for diagnostics but pose risks due to radiation exposure. Low-dose CT (LDCT) mitigates these risks but introduces noise and artifacts that compromise diagnostic accuracy. While deep learning methods,...

Machine-learning modeL based on computed tomography body composition analysis for the estimation of resting energy expenditure: A pilot study.

Clinical nutrition ESPEN
BACKGROUND & AIMS: The assessment of resting energy expenditure (REE) is a challenging task with the current existing methods. The reference method, indirect calorimetry (IC), is not widely available, and other surrogates, such as equations and bioim...

Integrating Large language models into radiology workflow: Impact of generating personalized report templates from summary.

European journal of radiology
OBJECTIVE: To evaluate feasibility of large language models (LLMs) to convert radiologist-generated report summaries into personalized report templates, and assess its impact on scan reporting time and quality.

Anatomical Considerations for Achieving Optimized Outcomes in Individualized Cochlear Implantation.

Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
HYPOTHESIS: Machine learning models can assist with the selection of electrode arrays required for optimal insertion angles.

Deep-learning based automated pancreas segmentation on CT scans of chronic pancreatitis patients.

European journal of radiology
OBJECTIVES: This study aimed to develop an artificial intelligence (AI)-based segmentation model for accurate delineation of the complex pancreas in patients with chronic pancreatitis (CP) using computer tomography (CT) scans obtained during routine ...