AIMC Topic: Brain Neoplasms

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[Fully Automatic Glioma Segmentation Algorithm of Magnetic Resonance Imaging Based on 3D-UNet With More Global Contextual Feature Extraction: An Improvement on Insufficient Extraction of Global Features].

Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
OBJECTIVE: The fully automatic segmentation of glioma and its subregions is fundamental for computer-aided clinical diagnosis of tumors. In the segmentation process of brain magnetic resonance imaging (MRI), convolutional neural networks with small c...

Deep CNNs for glioma grading on conventional MRIs: Performance analysis, challenges, and future directions.

Mathematical biosciences and engineering : MBE
The increasing global incidence of glioma tumors has raised significant healthcare concerns due to their high mortality rates. Traditionally, tumor diagnosis relies on visual analysis of medical imaging and invasive biopsies for precise grading. As a...

Added prognostic value of 3D deep learning-derived features from preoperative MRI for adult-type diffuse gliomas.

Neuro-oncology
BACKGROUND: To investigate the prognostic value of spatial features from whole-brain MRI using a three-dimensional (3D) convolutional neural network for adult-type diffuse gliomas.

Use of artificial intelligence and radio genomics in neuroradiology and the future of brain tumour imaging and surgical planning in low- and middleincome countries.

JPMA. The Journal of the Pakistan Medical Association
Brain tumour diagnosis involves assessing various radiological and histopathological parameters. Imaging modalities are an excellent resource for disease monitoring. However, manual inspection of imaging is laborious, and performance varies depending...

Protocol: revolutionizing central nervous system tumour diagnosis in low- and middle-income countries: an innovative observational study on intraoperative smear and deep learning.

JPMA. The Journal of the Pakistan Medical Association
OBJECTIVE: The aim of this study is to assess the feasibility and implementation of a novel approach for intraoperative brain smears within the operating room, which is augmented with deep learning technology.

Insight into deep learning for glioma IDH medical image analysis: A systematic review.

Medicine
BACKGROUND: Deep learning techniques explain the enormous potential of medical image analysis, particularly in digital pathology. Concurrently, molecular markers have gained increasing significance over the past decade in the context of glioma patien...

Development and validation of a multi-modality fusion deep learning model for differentiating glioblastoma from solitary brain metastases.

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
OBJECTIVES: Glioblastoma (GBM) and brain metastases (BMs) are the two most common malignant brain tumors in adults. Magnetic resonance imaging (MRI) is a commonly used method for screening and evaluating the prognosis of brain tumors, but the specifi...

Deep learning links localized digital pathology phenotypes with transcriptional subtype and patient outcome in glioblastoma.

GigaScience
BACKGROUND: Deep learning has revolutionized medical image analysis in cancer pathology, where it had a substantial clinical impact by supporting the diagnosis and prognostic rating of cancer. Among the first available digital resources in the field ...

Computational Modeling and AI in Radiation Neuro-Oncology and Radiosurgery.

Advances in experimental medicine and biology
The chapter explores the extensive integration of artificial intelligence (AI) in healthcare systems, with a specific focus on its application in stereotactic radiosurgery. The rapid evolution of AI technology has led to promising developments in thi...

Machine and Deep Learning in Hyperspectral Fluorescence-Guided Brain Tumor Surgery.

Advances in experimental medicine and biology
Malignant glioma resection is often the first line of treatment in neuro-oncology. During glioma surgery, the discrimination of tumor's edges can be challenging at the infiltration zone, even by using surgical adjuncts such as fluorescence guidance (...