AIMC Topic: Tomography, X-Ray Computed

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[Current CT developments in imaging of pancreatic diseases].

Radiologie (Heidelberg, Germany)
BACKGROUND: Diseases of the pancreas are often diagnosed late and can have fatal consequences for patients.

A narrative review of radiomics and deep learning advances in neuroblastoma: updates and challenges.

Pediatric radiology
Neuroblastoma is an extremely heterogeneous tumor that commonly occurs in children. The diagnosis and treatment of this tumor pose considerable challenges due to its varied clinical presentations and intricate genetic aberrations. Presently, various ...

Localization of early infarction on non-contrast CT images in acute ischemic stroke with deep learning approach.

Scientific reports
Localization of early infarction on first-line Non-contrast computed tomogram (NCCT) guides prompt treatment to improve stroke outcome. Our previous study has shown a good performance in the identification of ischemic injury on NCCT. In the present s...

Comparison of two deep-learning image reconstruction algorithms on cardiac CT images: A phantom study.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to compare the performance of Precise IQ Engine (PIQE) and Advanced intelligent Clear-IQ Engine (AiCE) algorithms on image-quality according to the dose level in a cardiac computed tomography (CT) protocol.

Machine learning and deep learning enabled age estimation on medial clavicle CT images.

International journal of legal medicine
The medial clavicle epiphysis is a crucial indicator for bone age estimation (BAE) after hand maturation. This study aimed to develop machine learning (ML) and deep learning (DL) models for BAE based on medial clavicle CT images and evaluate the perf...

Multi-class deep learning architecture for classifying lung diseases from chest X-Ray and CT images.

Scientific reports
Medical imaging is considered a suitable alternative testing method for the detection of lung diseases. Many researchers have been working to develop various detection methods that have aided in the prevention of lung diseases. To better understand t...

Differentiating adrenal metastases from benign lesions with multiphase CT imaging: Deep learning could play an active role in assisting radiologists.

European journal of radiology
OBJECTIVES: To develop and externally validate multiphase CT-based deep learning (DL) models for differentiating adrenal metastases from benign lesions.

Applications of machine learning and deep learning in SPECT and PET imaging: General overview, challenges and future prospects.

Pharmacological research
The integration of positron emission tomography (PET) and single-photon emission computed tomography (SPECT) imaging techniques with machine learning (ML) algorithms, including deep learning (DL) models, is a promising approach. This integration enha...

Cross-Domain Unpaired Learning for Low-Dose CT Imaging.

IEEE journal of biomedical and health informatics
Supervised deep-learning techniques with paired training datasets have been widely studied for low-dose computed tomography (LDCT) imaging with excellent performance. However, the paired training datasets are usually difficult to obtain in clinical r...