Glioblastoma is among the most aggressive brain tumors in adults, characterized by patient-specific invasion patterns driven by the underlying brain microstructure. In this work, we present a proof-of-concept for a mathematical model of GBL growth, e...
PURPOSE: Sodium neuroimaging provides unique insights into the cellular and metabolic properties of brain tumors. However, at 3T, sodium neuroimaging MRI's low signal-to-noise ratio (SNR) and resolution discourages routine clinical use. We evaluated ...
BACKGROUND: Novel diagnostic criteria for glioblastoma (GBM) in the 2021 WHO classification emphasize the importance of integrating pathological and molecular features. Pathomics, which involves the extraction of digital pathology data, is gaining si...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Jun 2, 2025
BACKGROUND: Multiparametric Magnetic Resonance Imaging (mpMRI) is the gold standard for diagnosing brain tumors, especially gliomas, which are difficult to segment due to their heterogeneity and varied sub-regions. While manual segmentation is time-c...
Glioblastoma (GBM) is a highly aggressive brain tumor with poor outcomes and limited treatment options. The telomerase reverse transcriptase (TERT) promoter mutation, one of the key biomarkers in GBM, is linked to tumor progression and prognosis. Thi...
Hyperspectral imaging (HSI) and machine learning (ML) have been employed in the medical field for classifying highly infiltrative brain tumours. Although existing HSI databases of in vivo human brains are available, they present two main deficiencies...
BACKGROUND: Despite significant advances in AI-driven medical diagnostics, the integration of large language models (LLMs) into psychiatric practice presents unique challenges. While LLMs demonstrate high accuracy in controlled settings, their perfor...
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
May 8, 2025
PURPOSE: Diffusion models (DMs) excel in pixel-level and spatial tasks and are proven feature extractors for 2D image discriminative tasks when pretrained. However, their capabilities in 3D MRI discriminative tasks remain largely untapped. This study...
IEEE journal of biomedical and health informatics
May 6, 2025
Multi-modal Magnetic Resonance Imaging (MRI) provide sufficient complementary information for brain tumor segmentation, however, most current approaches rely on complete modalities and may collapse with incomplete modalities. Moreover, most existing ...
IEEE journal of biomedical and health informatics
May 6, 2025
In the context of contemporary artificial intelligence, increasing deep learning (DL) based segmentation methods have been recently proposed for brain tumor segmentation (BraTS) via analysis of multi-modal MRI. However, known DL-based works usually d...
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