BACKGROUND: The intersection of artificial intelligence and medical image analysis has ushered in a new era of innovation and changed the landscape of brain tumor detection and diagnosis. Correct detection and classification of brain tumors based on ...
BACKGROUND: A single learning algorithm can produce deep learning-based image segmentation models that vary in performance purely due to random effects during training. This study assessed the effect of these random performance fluctuations on the re...
Hematoxylin and eosin (H&E) staining is a crucial technique for diagnosing glioma, allowing direct observation of tissue structures. However, the H&E staining workflow necessitates intricate processing, specialized laboratory infrastructures, and spe...
Brain tumor detection in clinical applications is a complex and challenging task due to the intricate structures of the human brain. Magnetic Resonance (MR) imaging is widely preferred for this purpose because of its ability to provide detailed image...
Physical and engineering sciences in medicine
Jul 30, 2024
Gamma Knife radiosurgery (GKRS) is a well-established technique in radiation therapy (RT) for treating small-size brain tumors. It administers highly concentrated doses during each treatment fraction, with even minor dose errors posing a significant ...
The process of brain tumour segmentation entails locating the tumour precisely in images. Magnetic Resonance Imaging (MRI) is typically used by doctors to find any brain tumours or tissue abnormalities. With the use of region-based Convolutional Neur...
Journal of magnetic resonance imaging : JMRI
Jul 29, 2024
This comprehensive review explores the role of deep learning (DL) in glioma segmentation using multiparametric magnetic resonance imaging (MRI) data. The study surveys advanced techniques such as multiparametric MRI for capturing the complex nature o...
Journal of imaging informatics in medicine
Jul 26, 2024
The analysis of medical images (MI) is an important part of advanced medicine as it helps detect and diagnose various diseases early. Classifying brain tumors through magnetic resonance imaging (MRI) poses a challenge demanding accurate models for ef...
Accurate prediction and grading of gliomas play a crucial role in evaluating brain tumor progression, assessing overall prognosis, and treatment planning. In addition to neuroimaging techniques, identifying molecular biomarkers that can guide the dia...
In the field of histopathology, many studies on the classification of whole slide images (WSIs) using artificial intelligence (AI) technology have been reported. We have studied the disease progression assessment of glioma. Adult-type diffuse gliomas...