Brain Cancer

An Efficient Multi-Scale Convolutional Neural Network Based Multi-Class Brain MRI Classification for SaMD.

A brain tumor is the growth of abnormal cells in certain brain tissues with a high mortality rate; t...

Clinical Validation of a Deep-Learning Segmentation Software in Head and Neck: An Early Analysis in a Developing Radiation Oncology Center.

BACKGROUND: Organs at risk (OARs) delineation is a crucial step of radiotherapy (RT) treatment plann...

Deep learning for brain metastasis detection and segmentation in longitudinal MRI data.

PURPOSE: Brain metastases (BM) occur frequently in patients with metastatic cancer. Early and accura...

A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation.

BACKGROUND: We describe and evaluate a deep network algorithm which automatically contours organs at...

The evaluation of the reduction of radiation dose via deep learning-based reconstruction for cadaveric human lung CT images.

To compare the quality of CT images of the lung reconstructed using deep learning-based reconstructi...

Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners.

PURPOSE: Attenuation correction is a critically important step in data correction in positron emissi...

A deep learning model for discriminating true progression from pseudoprogression in glioblastoma patients.

INTRODUCTION: Glioblastomas (GBMs) are highly aggressive tumors. A common clinical challenge after s...

Deep learning methods for enhancing cone-beam CT image quality toward adaptive radiation therapy: A systematic review.

The use of deep learning (DL) to improve cone-beam CT (CBCT) image quality has gained popularity as ...

A Feasibility Study on Deep Learning Based Brain Tumor Segmentation Using 2D Ellipse Box Areas.

In most deep learning-based brain tumor segmentation methods, training the deep network requires ann...

Emphysema Quantification Using Ultra-Low-Dose Chest CT: Efficacy of Deep Learning-Based Image Reconstruction.

Background and Objectives: Although reducing the radiation dose level is important during diagnostic...

Digital skills of therapeutic radiographers/radiation therapists - Document analysis for a European educational curriculum.

INTRODUCTION: It is estimated that around 50% of cancer patients require Radiotherapy (RT) at some p...

The Effect of Salvage Radiation Therapy on Survival, Functional Outcomes, and Quality of Life in Men with Persistent Prostate-specific Antigen After Robot-Assisted Radical Prostatectomy: Which Patient Benefits More?

PURPOSE: The aim of this study was to evaluate the effect of salvage radiation therapy (sRT) on surv...

A Pipeline for the Implementation and Visualization of Explainable Machine Learning for Medical Imaging Using Radiomics Features.

Machine learning (ML) models have been shown to predict the presence of clinical factors from medica...

A deep learning and Monte Carlo based framework for bioluminescence imaging center of mass-guided glioblastoma targeting.

Bioluminescence imaging (BLI) is a valuable tool for non-invasive monitoring of glioblastoma multifo...

Predicting the outcome of radiotherapy in brain metastasis by integrating the clinical and MRI-based deep learning features.

BACKGROUND: A considerable proportion of metastatic brain tumors progress locally despite stereotact...

Fast intraoperative histology-based diagnosis of gliomas with third harmonic generation microscopy and deep learning.

Management of gliomas requires an invasive treatment strategy, including extensive surgical resectio...

Editorial for "Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning".

Fully Automated MRI Segmentation and Volumetric Measurement of Intracranial Meningioma Using Deep Learning.

BACKGROUND: Accurate and rapid measurement of the MRI volume of meningiomas is essential in clinical...

Diagnosis of Brain Tumor Using Light Weight Deep Learning Model with Fine-Tuning Approach.

Brain cancer is a rare and deadly disease with a slim chance of survival. One of the most important ...

A deep learning model designed for Raman spectroscopy with a novel hyperparameter optimization method.

Raman spectroscopy is a spectroscopic technique typically used to determine vibrational modes of mol...

A state-of-the-art technique to perform cloud-based semantic segmentation using deep learning 3D U-Net architecture.

Glioma is the most aggressive and dangerous primary brain tumor with a survival time of less than 14...