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 …

Emergency neuroradiology provides rapid diagnostic decision-making and guidance for
management for a wide range of acute conditions involving the brain, head and neck, and …

Diagnostic imaging, particularly MRI, plays a key role in the evaluation of many spine
pathologies. Recent progress in artificial intelligence and its subset, machine learning, has …

Convolutional Neural Networks are being increasingly applied to the detection of anomalies
in Computed Tomographies (CTs). The goal of this paper is to implement an automated …

Spinal bone lesions encompass a wide array of pathologies, spanning from benign
abnormalities to aggressive malignancies, such as diffusely localized metastases. Early …

Rationale and objectives Metastatic epidural masses are an important radiological finding.
The purpose of this study is to determine factors associated with non-reporting of …

Introduction Metastatic spinal cord compression (MSCC) is a disastrous complication of
advanced malignancy. A deep learning (DL) algorithm for MSCC classification on CT could …

Purpose To develop a deep learning (DL) model for epidural spinal cord compression
(ESCC) on CT, which will aid earlier ESCC diagnosis for less experienced clinicians …

Simple Summary Early diagnosis of metastatic epidural spinal cord compression (MESCC)
is vital to prevent paralysis. Staging CT scans are performed routinely in cancer patients and …

Emergency neuroradiology provides rapid diagnostic decision-making and guidance for
management for a wide range of acute conditions involving the brain, head and neck, and …