Simple Summary Spinal metastasis is the most common malignant disease of the spine, and
its early diagnosis and treatment is important to prevent complications and improve quality of …

Simple Summary Distinguishing between benign vs. malignant bone lesions is often difficult
on imaging. Many bone lesions are infrequent or rarely seen, and often only specialist …

Objective To establish and evaluate the 3D U-Net model for automated segmentation and
detection of pelvic bone metastases in patients with prostate cancer (PCa) using diffusion …

Background: Artificial Intelligence (AI)-based analysis represents an evolving medical field.
In the last few decades, several studies have reported the diagnostic efficiency of AI applied …

Simple Summary In recent years, advances in deep learning have transformed the analysis
of medical imaging, especially in spine oncology. Computed Tomography (CT) imaging is …

Simple Summary Artificial intelligence (AI) is gaining more and more attention in radiology.
The efficiency of AI-based algorithms to solve specific problems is, in some cases, far …

Background The number of focal liver lesions (FLLs) detected by imaging has increased
worldwide, highlighting the need to develop a robust, objective system for automatically …

Recently, radiomics and deep learning have gained attention as methods for computerized
image analysis. Radiomics and deep learning can perform diagnostic or predictive tasks …

Neuroendocrine tumors (NETs) are relatively rare neoplasms displaying heterogeneous
clinical behavior, ranging from indolent to aggressive forms. Patients diagnosed with NETs …

Simple Summary Quantification of liver metastases on imaging is of utmost importance in
therapy response assessment, wherein gadoxetic acid (Gd-EOB)-enhanced magnetic …