Latest AI and machine learning research in brain cancer for healthcare professionals.
Gliomas are the most common tumor in the central nervous system in adults, with glioblastoma (GBM) r...
To develop and evaluate a 3D Prompt-ResUNet module that utilized the prompt-based model combined wit...
RATIONALE AND OBJECTIVES: Recent radiomics studies on predicting pathological outcomes of glioma hav...
BACKGROUND AND PURPOSE: During the ESTRO 2023 physics workshop on "AI for the fully automated radiot...
INTRODUCTION: Gliomas are the most common and aggressive type of primary brain tumor, with a poor pr...
AIM: We evaluated the quality of noncontrast chest computed tomography (CT) for pediatric patients a...
RATIONALE AND OBJECTIVES: This study evaluated the performance of super-resolution deep learning-bas...
BACKGROUND: Salvage radiation therapy (sRT) is often the sole curative option in patients with bioch...
Pediatric head trauma is a significant cause of morbidity and mortality, with children, particularly...
RATIONALE AND OBJECTIVES: Traumatic neuroradiological emergencies necessitate rapid and accurate dia...
BACKGROUND: Long-lasting efforts have been made to reduce radiation dose and thus the potential radi...
PURPOSE: To investigate the application value of support vector machine (SVM) model based on diffusi...
An early detection of lung tumors is critical for better treatment results, and CT scans can reveal ...
BACKGROUND: Radiation dose should be as low as reasonably achievable. With the invention of photon-c...
How to develop contrast agents for cancer theranostics is a meaningful and challenging endeavor, and...
BACKGROUND AND PURPOSE: CT imaging exposes patients to ionizing radiation. MR imaging is radiation f...
In computed tomography (CT) imaging, optimizing the balance between radiation dose and image quality...
Brain tumors pose significant global health concerns due to their high mortality rates and limited t...
Acute radiation dermatitis (ARD) is a common and distressing issue for cancer patients undergoing ra...
OBJECTIVE: Research into the effectiveness and applicability of deep learning, radiomics, and their ...
BACKGROUND: Deep learning reconstruction (DLR) with denoising has been reported as potentially impro...