Accurate differentiation of pseudoprogression (PsP) from True Progression (TP) following radiotherapy (RT) in glioblastoma patients is crucial for optimal treatment planning. However, this task remains challenging due to the overlapping imaging chara...
Studies in health technology and informatics
May 15, 2025
Employing a whole-brain (WB) mask as a region of interest for extracting radiomic features is a feasible, albeit less common, approach in neuro-oncology research. This study aims to evaluate the relationship between WB radiomic features, derived from...
Studies in health technology and informatics
May 15, 2025
The effective detection of brain tumors is closely linked to their timely diagnosis and treatment which can help in the prevention of deaths and in improving the quality of life. The objective of this paper is to present an enhanced YOLO (You Look On...
Studies in health technology and informatics
May 15, 2025
Manual segmentation of histopathological images is both resource-intensive and prone to human error, particularly when dealing with challenging tumor types like Glioblastoma (GBM), an aggressive and highly heterogeneous brain tumor. The fuzzy borders...
We developed and validated a magnetic resonance imaging (MRI)-based radiomics model for the classification of high-grade glioma (HGG) and determined the optimal machine learning (ML) approach. This retrospective analysis included 184 patients (59 gra...
BACKGROUND: Glioblastoma (GBM) is the most aggressive adult primary brain cancer, characterized by significant heterogeneity, posing challenges for patient management, treatment planning, and clinical trial stratification.
Stereotactic radiosurgery (SRS) is a non-invasive technique that is transforming the management of benign intracranial lesions through its precision and preservation of healthy tissues. It is effective for meningiomas, trigeminal neuralgia (TN), pitu...
Deep learning, particularly convolutional neural networks (CNNs), has proven valuable for brain tumor classification, aiding diagnostic and therapeutic decisions in medical imaging. Despite their accuracy, these models are vulnerable to adversarial a...
Biomedical physics & engineering express
May 13, 2025
Glioma is one of the most lethal types of brain tumors, accounting for approximately 33% of all diagnosed brain tumor cases. Accurate segmentation and classification are crucial for precise glioma characterization, emphasizing early detection of mali...
Journal of computer assisted tomography
May 13, 2025
OBJECTIVE: The aim of this study was to evaluate various radiomics-based machine learning classification models using the apparent diffusion coefficient (ADC) and cerebral blood flow (CBF) maps for differentiating between low-grade gliomas (LGGs) and...
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