AIMC Topic: Radiosurgery
Clear Filters Showing 71 to 80 of 152 articles
Deep convolutional neural networks for automated segmentation of brain metastases trained on clinical data.
Radiation oncology (London, England)
Apr 20, 2020
INTRODUCTION: Deep learning-based algorithms have demonstrated enormous performance in segmentation of medical images. We collected a dataset of multiparametric MRI and contour data acquired for use in radiosurgery, to evaluate the performance of dee...
Computer-aided Detection of Brain Metastases in T1-weighted MRI for Stereotactic Radiosurgery Using Deep Learning Single-Shot Detectors.
Radiology
Mar 17, 2020
Background Brain metastases are manually identified during stereotactic radiosurgery (SRS) treatment planning, which is time consuming and potentially challenging. Purpose To develop and investigate deep learning (DL) methods for detecting brain meta...
Hypofractionated Robotic Stereotactic Radiosurgery for Vagal Paragangliomas: A Novel Treatment Strategy for Cranial Nerve Preservation.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Mar 3, 2020
OBJECTIVE: To provide the first description of hypofractionated stereotactic radiosurgery (SRS) and evaluate tumor control and safety for vagal paragangliomas (VPs), which begin at the skull base but often have significant extracranial extension.
Performance assessment of a new optimization system for robotic SBRT MLC-based plans.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Feb 20, 2020
PURPOSE: To assess the performance of a new optimization system, VOLO, for CyberKnife MLC-based SBRT plans in comparison with the existing Sequential optimizer.
An investigation of machine learning methods in delta-radiomics feature analysis.
PloS one
Dec 13, 2019
PURPOSE: This study aimed to investigate the effectiveness of using delta-radiomics to predict overall survival (OS) for patients with recurrent malignant gliomas treated by concurrent stereotactic radiosurgery and bevacizumab, and to investigate the...
Deep segmentation networks predict survival of non-small cell lung cancer.
Scientific reports
Nov 21, 2019
Non-small-cell lung cancer (NSCLC) represents approximately 80-85% of lung cancer diagnoses and is the leading cause of cancer-related death worldwide. Recent studies indicate that image-based radiomics features from positron emission tomography/comp...
Radiosurgery
Positron Emission Tomography Computed Tomography
Neoplasm Staging
Male
Middle Aged
Radiopharmaceuticals
Lung
Datasets as Topic
Retrospective Studies
Image Processing, Computer-Assisted
Humans
Deep Learning
Female
Lung Neoplasms
Prognosis
Aged
Treatment Outcome
Aged, 80 and over
Carcinoma, Non-Small-Cell Lung
Survival Rate
Predictive Value of Tests
A simple knowledge-based tool for stereotactic radiosurgery pre-planning.
Journal of applied clinical medical physics
Nov 19, 2019
We studied the dosimetry of single-isocenter treatment plans generated to treat a solitary intracranial lesion using linac-based stereotactic radiosurgery (SRS). A common metric for evaluating SRS plan quality is the volume of normal brain tissue irr...
Effect of Radiation Doses to the Heart on Survival for Stereotactic Ablative Radiotherapy for Early-stage Non-Small-cell Lung Cancer: An Artificial Neural Network Approach.
Clinical lung cancer
Oct 21, 2019
INTRODUCTION: The cardiac radiation dose is an important predictor of cardiac toxicity and overall survival (OS) for patients with locally advanced non-small-cell lung cancer (NSCLC). However, radiation-induced cardiac toxicity among patients with ea...
Image-Guided Robotic Radiosurgery for Treatment of Recurrent Grade II and III Meningiomas. A Single-Center Study.
World neurosurgery
Jul 12, 2019
OBJECTIVE: Stereotactic radiosurgery (SRS) has been increasingly applied for malignant meningiomas as an alternative to conventionally fractioned radiation therapy. We performed a retrospective analysis of an institutional patient cohort with maligna...
An image-based deep learning framework for individualizing radiotherapy dose.
The Lancet. Digital health
Jun 27, 2019
BACKGROUND: Radiotherapy continues to be delivered uniformly without consideration of individual tumor characteristics. To advance toward more precise treatments in radiotherapy, we queried the lung computed tomography (CT)-derived feature space to i...
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