Brain Cancer

Automated Meningioma Segmentation in Multiparametric MRI : Comparable Effectiveness of a Deep Learning Model and Manual Segmentation.

PURPOSE: Volumetric assessment of meningiomas represents a valuable tool for treatment planning and ...

Imaging-Based Algorithm for the Local Grading of Glioma.

BACKGROUND AND PURPOSE: Gliomas are highly heterogeneous tumors, and optimal treatment depends on id...

A quantitative model based on clinically relevant MRI features differentiates lower grade gliomas and glioblastoma.

OBJECTIVES: To establish a quantitative MR model that uses clinically relevant features of tumor loc...

A deep learning approach to radiation dose estimation.

Currently methods for predicting absorbed dose after administering a radiopharmaceutical are rather ...

User-controlled pipelines for feature integration and head and neck radiation therapy outcome predictions.

PURPOSE: Precision cancer medicine is dependent on accurate prediction of disease and treatment outc...

Patient-Level Effectiveness Prediction Modeling for Glioblastoma Using Classification Trees.

OBJECTIVES: Little research has been done in pharmacoepidemiology on the use of machine learning for...

Machine learning-based prediction of glioma margin from 5-ALA induced PpIX fluorescence spectroscopy.

Gliomas are infiltrative brain tumors with a margin difficult to identify. 5-ALA induced PpIX fluore...

Overlooked pitfalls in multi-class machine learning classification in radiation oncology and how to avoid them.

In radiation oncology, Machine Learning classification publications are typically related to two out...

Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning.

PURPOSE: Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Curr...

A fast deep learning approach for beam orientation optimization for prostate cancer treated with intensity-modulated radiation therapy.

PURPOSE: Beam orientation selection, whether manual or protocol-based, is the current clinical stand...

DC-AL GAN: Pseudoprogression and true tumor progression of glioblastoma multiform image classification based on DCGAN and AlexNet.

PURPOSE: Pseudoprogression (PsP) occurs in 20-30% of patients with glioblastoma multiforme (GBM) aft...

Publication Landscape Analysis on Gliomas: How Much Has Been Done in the Past 25 Years?

The body of glioma-related literature has grown significantly over the past 25 years. Despite this ...

Real-time prediction of tumor motion using a dynamic neural network.

Radiation dose delivery into the thoracic and abdomen cavities during radiotherapy treatment is a ch...

Deep Learning of Imaging Phenotype and Genotype for Predicting Overall Survival Time of Glioblastoma Patients.

Glioblastoma (GBM) is the most common and deadly malignant brain tumor. For personalized treatment, ...

A Multiple-Instance Learning-Based Convolutional Neural Network Model to Detect the Mutation in the Histopathology Images of Glioma Tissues.

Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network.

Identification of genotypes is crucial for treatment of glioma. Here, we developed a method to predi...

Cardiac substructure segmentation with deep learning for improved cardiac sparing.

PURPOSE: Radiation dose to cardiac substructures is related to radiation-induced heart disease. Howe...

Intracatheter Tissue Plasminogen Activator for Chronic Subdural Hematomas after Failed Bedside Twist Drill Craniostomy: A Retrospective Review.

Introduction Chronic subdural hematomas (cSDH) are common in neurosurgery with various symptoms and ...

Prediction of lower-grade glioma molecular subtypes using deep learning.

INTRODUCTION: It is useful to know the molecular subtype of lower-grade gliomas (LGG) when deciding ...

Efficient identification of novel anti-glioma lead compounds by machine learning models.

Glioblastoma multiforme (GBM) is the most devastating and widespread primary central nervous system ...

Deep Transfer Learning and Radiomics Feature Prediction of Survival of Patients with High-Grade Gliomas.

BACKGROUND AND PURPOSE: Patient survival in high-grade glioma remains poor, despite the recent devel...