BACKGROUND: Perfusion magnetic resonance imaging (MRI)s plays a central role in the diagnosis and monitoring of neurovascular or neurooncological disease. However, conventional processing techniques are limited in their ability to capture relevant ch...
The detection and tracking of metastatic cancer over the lifetime of a patient remains a major challenge in clinical trials and real-world care. Advances in deep learning combined with massive datasets may enable the development of tools that can add...
Journal of applied clinical medical physics
Sep 16, 2024
PURPOSE: We have built a novel AI-driven QA method called AutoConfidence (ACo), to estimate segmentation confidence on a per-voxel basis without gold standard segmentations, enabling robust, efficient review of automated segmentation (AS). We have de...
PURPOSE: To investigate the application value of support vector machine (SVM) model based on diffusion-weighted imaging (DWI), dynamic contrast-enhanced (DCE) and amide proton transfer- weighted (APTW) imaging in predicting isocitrate dehydrogenase 1...
PURPOSE: To shorten CEST acquisition time by leveraging Z-spectrum undersampling combined with deep learning for CEST map construction from undersampled Z-spectra.
BACKGROUND: The pretherapeutic differentiation of subtypes of primary intracranial germ cell tumours (iGCTs), including germinomas (GEs) and nongerminomatous germ cell tumours (NGGCTs), is essential for clinical practice because of distinct treatment...
. Approximately 57% of non-small cell lung cancer (NSCLC) patients face a 20% risk of brain metastases (BMs). The delivery of drugs to the central nervous system is challenging because of the blood-brain barrier, leading to a relatively poor prognosi...
Journal of medical imaging and radiation sciences
Sep 9, 2024
INTRODUCTION: The complexity of diffuse gliomas relies on advanced imaging techniques like MRI to understand their heterogeneity. Utilizing the UCSF-PDGM dataset, this study harnesses MRI techniques, radiomics, and AI to analyze diffuse gliomas for o...
AJNR. American journal of neuroradiology
Sep 9, 2024
BACKGROUND AND PURPOSE: Feature variability in radiomics studies due to technical and magnet strength parameters is well-known and may be addressed through various preprocessing methods. However, very few studies have evaluated the downstream impact ...