Latest AI and machine learning research in brain cancer for healthcare professionals.
BACKGROUND: Radiotherapy has been crucial in prostate cancer treatment. However, manual segmentation...
A precise radiotherapy plan is crucial to ensure accurate segmentation of glioblastomas (GBMs) for r...
Head and neck squamous cell carcinoma (HNSCC) is a complex malignancy that requires a multidisciplin...
PURPOSE: Convolutional Neural Networks (CNNs) have emerged as transformative tools in the field of r...
PURPOSE: In the rapidly expanding field of artificial intelligence (AI) there is a wealth of literat...
Third harmonic generation (THG) microscopy shows great potential for instant pathology of brain tumo...
BackgroundGlioma is one of the most common primary brain tumors. The presence of the telomerase reve...
Artificial intelligence can standardize and automatize highly demanding procedures, such as manual s...
This study explores the impact of densely-ionizing radiation on non-cancer and cancer diseases, focu...
Hematoxylin and eosin (H&E) staining is a crucial technique for diagnosing glioma, allowing direct o...
OBJECTIVE: To investigate the accuracy of machine learning (ML) algorithms in stratifying risk of pr...
PURPOSE: Organ-at-risk segmentation is essential in adaptive radiotherapy (ART). Learning-based auto...
Geometric distortions in brain MRI images arising from susceptibility artifacts at air-tissue interf...
Gamma Knife radiosurgery (GKRS) is a well-established technique in radiation therapy (RT) for treati...
This comprehensive review explores the role of deep learning (DL) in glioma segmentation using multi...
Accurate prediction and grading of gliomas play a crucial role in evaluating brain tumor progression...
Lung cancer is the leading cause of cancer-related deaths globally, with non-small cell lung cancer ...
PURPOSE: Currently, precise patient body weight (BW) at the time of diagnostic imaging cannot always...
In the field of histopathology, many studies on the classification of whole slide images (WSIs) usin...
BACKGROUND: It is uncertain which biological features underpin the response of rectal cancer (RC) to...
PURPOSE: To develop a combined radiomics and deep learning (DL) model in predicting radiation esopha...