AIMC Topic: Tomography, X-Ray Computed

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Development of a deep learning based approach for multi-material decomposition in spectral CT: a proof of principle in silico study.

Scientific reports
Conventional approaches to material decomposition in spectral CT face challenges related to precise algorithm calibration across imaged conditions and low signal quality caused by variable object size and reduced dose. In this proof-of-principle stud...

Immune checkpoint inhibitor-related pneumonitis: From guidelines to the front lines.

Respiratory investigation
Immune checkpoint inhibitors (ICIs) have changed cancer treatment, evoking durable responses in various cancers. However, their immune-mediated mechanisms can lead to unique toxicities known as immune-related adverse events (irAEs), among which ICI-r...

AI-driven framework for automated detection of kidney stones in CT images: integration of deep learning architectures and transformers.

Biomedical physics & engineering express
. Kidney stones, a prevalent urological condition, associated with acute pain requires prompt and precise diagnosis for optimal therapeutic intervention. While computed tomography (CT) imaging remains the definitive diagnostic modality, manual interp...

Combined nomogram for differentiating adrenal pheochromocytoma from large-diameter lipid-poor adenoma using multiphase CT radiomics and clinico-radiological features.

BMC medical imaging
BACKGROUND AND OBJECTIVE: Adrenal incidentalomas (AIs) are predominantly adrenal adenomas (80%), with a smaller proportion (7%) being pheochromocytomas(PHEO). Adenomas are typically non-functional tumors managed through observation or medication, wit...

A dual self-attentive transformer U-Net model for precise pancreatic segmentation and fat fraction estimation.

BMC medical imaging
Accurately segmenting the pancreas from abdominal computed tomography (CT) images is crucial for detecting and managing pancreatic diseases, such as diabetes and tumors. Type 2 diabetes and metabolic syndrome are associated with pancreatic fat accumu...

Early prediction of proton therapy dose distributions and DVHs for hepatocellular carcinoma using contour-based CNN models from diagnostic CT and MRI.

Radiation oncology (London, England)
BACKGROUND: Proton therapy is commonly used for treating hepatocellular carcinoma (HCC); however, its feasibility can be challenging to assess in large tumors or those adjacent to critical organs at risk (OARs), which are typically assessed only afte...

Adapting foundation models for rapid clinical response: intracerebral hemorrhage segmentation in emergency settings.

Scientific reports
Intracerebral hemorrhage (ICH) is a medical emergency that demands rapid and accurate diagnosis for optimal patient management. Hemorrhagic lesions' segmentation on CT scans is a necessary first step for acquiring quantitative imaging data that are b...

Transfer learning based deep architecture for lung cancer classification using CT image with pattern and entropy based feature set.

Scientific reports
Early detection of lung cancer, which remains one of the leading causes of death worldwide, is important for improved prognosis, and CT scanning is an important diagnostic modality. Lung cancer classification according to CT scan is challenging since...

The dosimetric impacts of ct-based deep learning autocontouring algorithm for prostate cancer radiotherapy planning dosimetric accuracy of DirectORGANS.

BMC urology
PURPOSE: In study, we aimed to dosimetrically evaluate the usability of a new generation autocontouring algorithm (DirectORGANS) that automatically identifies organs and contours them directly in the computed tomography (CT) simulator before creating...