AIMC Topic: Tomography, X-Ray Computed

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KUB-UNet: Segmentation of Organs of Urinary System from a KUB X-ray Image.

Computer methods and programs in biomedicine
PURPOSE: The alarming increase in diseases of urinary system is a cause of concern for the populace and health experts. The traditional techniques used for the diagnosis of these diseases are inconvenient for patients, require high cost, and addition...

Comparison of lung CT number and airway dimension evaluation capabilities of ultra-high-resolution CT, using different scan modes and reconstruction methods including deep learning reconstruction, with those of multi-detector CT in a QIBA phantom study.

European radiology
OBJECTIVE: Ultra-high-resolution CT (UHR-CT), which can be applied normal resolution (NR), high-resolution (HR), and super-high-resolution (SHR) modes, has become available as in conjunction with multi-detector CT (MDCT). Moreover, deep learning reco...

Emphysema Quantification Using Ultra-Low-Dose Chest CT: Efficacy of Deep Learning-Based Image Reconstruction.

Medicina (Kaunas, Lithuania)
Background and Objectives: Although reducing the radiation dose level is important during diagnostic computed tomography (CT) applications, effective image quality enhancement strategies are crucial to compensate for the degradation that is caused by...

Deep learning with multiresolution handcrafted features for brain MRI segmentation.

Artificial intelligence in medicine
The segmentation of magnetic resonance (MR) images is a crucial task for creating pseudo computed tomography (CT) images which are used to achieve positron emission tomography (PET) attenuation correction. One of the main challenges of creating pseud...

Detection of Incidental Pulmonary Embolism on Conventional Contrast-Enhanced Chest CT: Comparison of an Artificial Intelligence Algorithm and Clinical Reports.

AJR. American journal of roentgenology
Artificial intelligence (AI) algorithms have shown strong performance for detection of pulmonary embolism (PE) on CT examinations performed using a dedicated protocol for PE detection. AI performance is less well studied for detecting PE on examinat...

Bone segmentation in contrast enhanced whole-body computed tomography.

Biomedical physics & engineering express
Segmentation of bone regions allows for enhanced diagnostics, disease characterisation and treatment monitoring in CT imaging. In contrast enhanced whole-body scans accurate automatic segmentation is particularly difficult as low dose whole body prot...

MRI-based and robot-assisted stereotactic biopsy with intraoperative CT imaging.

Acta neurochirurgica
BACKGROUND: As a pioneer center in the field of stereotaxy, Sainte-Anne school has always advocated the use of intraoperative imaging for stereotactic procedures to optimize both safety and accuracy. With the advent of intraoperative mobile CT unit, ...

Deep learning versus iterative reconstruction on image quality and dose reduction in abdominal CT: a live animal study.

Physics in medicine and biology
While simulated low-dose CT images and phantom studies cannot fully approximate subjective and objective effects of deep learning (DL) denoising on image quality, live animal models may afford this assessment. This study is to investigate the potenti...

A Novel Deep Learning and Ensemble Learning Mechanism for Delta-Type COVID-19 Detection.

Frontiers in public health
Recently, the novel coronavirus disease 2019 (COVID-19) has posed many challenges to the research community by presenting grievous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that results in a huge number of mortalities and high morb...