Brain Cancer

Synthesis of gadolinium-enhanced glioma images on multisequence magnetic resonance images using contrastive learning.

BACKGROUND: Gadolinium-based contrast agents are commonly used in brain magnetic resonance imaging (...

Deep Learning Glioma Grading with the Tumor Microenvironment Analysis Protocol for Comprehensive Learning, Discovering, and Quantifying Microenvironmental Features.

Gliomas are primary brain tumors that arise from neural stem cells, or glial precursors. Diagnosis o...

Research Progress of Artificial Intelligence in the Grading and Classification of Meningiomas.

A meningioma is a common primary central nervous system tumor. The histological features of meningio...

Quantitative and Visual Analysis of Data Augmentation and Hyperparameter Optimization in Deep Learning-Based Segmentation of Low-Grade Glioma Tumors Using Grad-CAM.

This study executes a quantitative and visual investigation on the effectiveness of data augmentatio...

Stratification of tumour cell radiation response and metabolic signatures visualization with Raman spectroscopy and explainable convolutional neural network.

Reprogramming of cellular metabolism is a driving factor of tumour progression and radiation therapy...

Machine learning application identifies plasma markers for proteinuria in metastatic colorectal cancer patients treated with Bevacizumab.

BACKGROUND AND OBJECTIVES: Proteinuria is a common complication after the application of bevacizumab...

Deep match: A zero-shot framework for improved fiducial-free respiratory motion tracking.

BACKGROUND AND PURPOSE: Motion management is essential to reduce normal tissue exposure and maintain...

dbCRAF: a curated knowledgebase for regulation of radiation response in human cancer.

Radiation therapy (RT) is one of the primary treatment modalities of cancer, with 40-60% of cancer p...

Bone age assessment based on three-dimensional ultrasound and artificial intelligence compared with paediatrician-read radiographic bone age: protocol for a prospective, diagnostic accuracy study.

INTRODUCTION: Radiographic bone age (BA) assessment is widely used to evaluate children's growth dis...

Visual Outcomes after Suprasellar Meningioma Resection: A Retrospective Cohort Study and a Machine Learning-Based Predictive Model.

 In this research, the authors provide a retrospective cohort study of 82 patients with suprasellar...

An Innovative Inducer of Platelet Production, Isochlorogenic Acid A, Is Uncovered through the Application of Deep Neural Networks.

(1) Background: Radiation-induced thrombocytopenia (RIT) often occurs in cancer patients undergoing ...

Ultra-low dose chest CT with silver filter and deep learning reconstruction significantly reduces radiation dose and retains quantitative information in the investigation and monitoring of lymphangioleiomyomatosis (LAM).

PURPOSE: Frequent CT scans to quantify lung involvement in cystic lung disease increases radiation e...

Auto-segmentation of Adult-Type Diffuse Gliomas: Comparison of Transfer Learning-Based Convolutional Neural Network Model vs. Radiologists.

Segmentation of glioma is crucial for quantitative brain tumor assessment, to guide therapeutic rese...

Deep learning segmentation of organs-at-risk with integration into clinical workflow for pediatric brain radiotherapy.

PURPOSE: Radiation therapy (RT) of pediatric brain cancer is known to be associated with long-term n...

Using deep learning-based denoising and iterative reconstruction to reduce radiation exposure - How low can we go?

Development and internal validation of machine learning models for personalized survival predictions in spinal cord glioma patients.

BACKGROUND CONTEXT: Numerous factors have been associated with the survival outcomes in patients wit...

A Review of deep learning methods for denoising of medical low-dose CT images.

To prevent patients from being exposed to excess of radiation in CT imaging, the most common solutio...

Exploring the role of large language models in radiation emergency response.

In recent times, the field of artificial intelligence (AI) has been transformed by the introduction ...

Deciphering the fibrotic process: mechanism of chronic radiation skin injury fibrosis.

This review explores the mechanisms of chronic radiation-induced skin injury fibrosis, focusing on t...

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BACKGROUND:: Efficient and accurate delineation of organs at risk (OARs) is a critical procedure for...

Deep learning-based algorithms for low-dose CT imaging: A review.

The computed tomography (CT) technique is extensively employed as an imaging modality in clinical se...