Brain Cancer

Novel Deep Learning Denoising Enhances Image Quality and Lowers Radiation Exposure in Interventional Bronchial Artery Embolization Cone Beam CT.

OBJECTIVES: In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT...

Cytotoxic activity of ethyl acetate extract of on MCF7 and T47D breast cancer cells.

One of the most cancers in women that can be fatal is breast cancer. Radiation therapy, chemotherapy...

Differentiation Between Glioblastoma and Metastatic Disease on Conventional MRI Imaging Using 3D-Convolutional Neural Networks: Model Development and Validation.

RATIONALE AND OBJECTIVES: Imaging-based differentiation between glioblastoma (GB) and brain metastas...

Editorial for "Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures".

Glioblastoma and Solitary Brain Metastasis: Differentiation by Integrating Demographic-MRI and Deep-Learning Radiomics Signatures.

BACKGROUND: Studies have shown that deep-learning radiomics (DLR) could help differentiate glioblast...

Deep learning catheter tip locations for photoacoustic-guided cardiac interventions.

SIGNIFICANCE: Interventional cardiac procedures often require ionizing radiation to guide cardiac ca...

Unsupervised machine learning models reveal predictive clinical markers of glioblastoma patient survival using white blood cell counts prior to initiating chemoradiation.

BACKGROUND: Glioblastoma is a malignant brain tumor requiring careful clinical monitoring even after...

Framework for Radiation Oncology Department-wide Evaluation and Implementation of Commercial Artificial Intelligence Autocontouring.

PURPOSE: Artificial intelligence (AI)-based autocontouring in radiation oncology has potential benef...

Exploring Capabilities of Large Language Models such as ChatGPT in Radiation Oncology.

PURPOSE: Technological progress of machine learning and natural language processing has led to the d...

Enhancing Safety in AI-Driven Cone Beam CT-based Online Adaptive Radiation Therapy: Development and Implementation of an Interdisciplinary Workflow.

PURPOSE: The emerging online adaptive radiation therapy (OART) treatment strategy based on cone beam...

Multi-class glioma segmentation on real-world data with missing MRI sequences: comparison of three deep learning algorithms.

This study tests the generalisability of three Brain Tumor Segmentation (BraTS) challenge models usi...

Current Strengths and Weaknesses of ChatGPT as a Resource for Radiation Oncology Patients and Providers.

PURPOSE: Chat Generative Pre-Trained Transformer (ChatGPT), an artificial intelligence program that ...

Screening the phytotoxicity of micro/nanoplastics through non-targeted metallomics with synchrotron radiation X-ray fluorescence and deep learning: Taking micro/nano polyethylene terephthalate as an example.

Microplastics (MPs) and nanoplastics (NPs) are global pollutants with emerging concerns. Methods to ...

Healthcare Professional Association Agency in Preparing for Artificial Intelligence: A Multiple-Case Study of Radiation Medicine and Medical Imaging in the Canadian context.

As artificial intelligence (AI) is increasingly integrated in healthcare, it is incumbent on healthc...

A transformer-based multi-task deep learning model for simultaneous infiltrated brain area identification and segmentation of gliomas.

BACKGROUND: The anatomical infiltrated brain area and the boundaries of gliomas have a significant i...

Predicting meningioma grades and pathologic marker expression via deep learning.

OBJECTIVES: To establish a deep learning (DL) model for predicting tumor grades and expression of pa...

Emerging trends in post-translational modification: Shedding light on Glioblastoma multiforme.

Recent multi-omics studies, including proteomics, transcriptomics, genomics, and metabolomics have r...

Interpreting deep learning models for glioma survival classification using visualization and textual explanations.

BACKGROUND: Saliency-based algorithms are able to explain the relationship between input image pixel...

Artificial Intelligence-Based Organ Delineation for Radiation Treatment Planning of Prostate Cancer on Computed Tomography.

PURPOSE: Meticulous manual delineations of the prostate and the surrounding organs at risk are neces...

Neuropathologist-level integrated classification of adult-type diffuse gliomas using deep learning from whole-slide pathological images.

Current diagnosis of glioma types requires combining both histological features and molecular charac...

MGMT promoter methylation status prediction using MRI scans? An extensive experimental evaluation of deep learning models.

The number of studies on deep learning for medical diagnosis is expanding, and these systems are oft...