Therapeutic Radiology

Enhancing Choroidal Nevus Position Identification through CNN-Based Segmentation of Eye Fundus Images.

Diagnosing choroidal nevus in color fundus images is challenging for clinicians not regularly practicing it. Machine learning (ML) has proven effective in detecting and analyzing such abnormalities with high accuracy and efficiencyThis research is part of a larger project to develop a decision support system for choroidal nevus diagnosis, focusing on creating a segmentation algorithm to identify k...

Patient Cranial Angle and Intrafractional Stability in CyberKnife Robotic Radiosurgery: A Retrospective Analysis.

The aim of this study was to investigate whether variations in cranial angles and treatment accuracy during CyberKnife robotic radiosurgery necessitate adjustment of the margins of the planning target volume. Data from 66 patients receiving CyberKnife treatment for brain tumors were retrospectively analyzed. Patients were immobilized using a thermoplastic mask and headrest. The cranial angle was...

Deep Learning-Based Prediction of Radiation Therapy Dose Distributions in Nasopharyngeal Carcinomas: A Preliminary Study Incorporating Multiple Features Including Images, Structures, and Dosimetry.

Intensity-modulated radiotherapy (IMRT) is currently the most important treatment method for nasopharyngeal carcinoma (NPC). This study aimed to enha...

Computational Modeling and AI in Radiation Neuro-Oncology and Radiosurgery.

The chapter explores the extensive integration of artificial intelligence (AI) in healthcare systems, with a specific focus on its application in ster...

Segmentation of Clinical Target Volume From CT Images for Cervical Cancer Using Deep Learning.

Segmentation of clinical target volume (CTV) from CT images is critical for cervical cancer brachytherapy, but this task is time-consuming, laborious...

Artificial Intelligence and Deep Learning for Brachytherapy.

In recent years, Artificial intelligence (AI), specifically deep-learning (DL) based methods, have been employed extensively to solve various problems...

Deep Learning using Pre-Brachytherapy MRI to Automatically Predict Applicator Induced Complex Uterine Deformation.

This novel deep-learning (DL) algorithm addresses the challenging task of predicting uterine shape and location when deformed from its natural anatomy...

Artificial intelligence can overcome challenges in brachytherapy treatment planning.

Deep Learning for Patient-Specific Quality Assurance: Predicting Gamma Passing Rates for IMRT Based on Delivery Fluence Informed by log Files.

In this study, we propose a deep learning-based approach to predict Intensity-modulated radiation therapy (IMRT) quality assurance (QA) gamma passing...

Robotic Radical Cystectomy Outcomes after Intervention for Prostate Cancer.

We evaluated patients who underwent treatment for prostate cancer and then subsequent robot-assisted radical cystectomy (RARC). Our objective was to ...

Monte Carlo Dose Calculation Using MRI Based Synthetic CT Generated by Fully Convolutional Neural Network for Gamma Knife Radiosurgery.

The aim of this work is to study the dosimetric effect from generated synthetic computed tomography (sCT) from magnetic resonance (MR) images using a ...

Knowledge-Based Planning for Intact Cervical Cancer.

Cervical cancer radiotherapy is often complicated by significant variability in the quality and consistency of treatment plans. Knowledge-based planni...

Automated Intensity Modulated Radiation Therapy Treatment Planning for Cervical Cancer Based on Convolution Neural Network.

PURPOSE: To develop and evaluate an automatic intensity-modulated radiation therapy (IMRT) program for cervical cancer, including a Convolution Neural...

A convolutional neural network approach for IMRT dose distribution prediction in prostate cancer patients.

The purpose of the study was to compare a 3D convolutional neural network (CNN) with the conventional machine learning method for predicting intensity...

Prediction of Response to Stereotactic Radiosurgery for Brain Metastases Using Convolutional Neural Networks.

BACKGROUND: It is unclear whether radiomic phenotypes of brain metastases (BM) are related to radiation therapy prognosis. This study assessed whether...

Photoacoustic Source Detection and Reflection Artifact Removal Enabled by Deep Learning.

Interventional applications of photoacoustic imaging typically require visualization of point-like targets, such as the small, circular, cross-section...

[A Software Platform of Treatment Planning System for Radiotherapy Snake Robot].

A software platform integrated of radiation treatment planning system and navigation system has been developed for a newly-developed snake robot. This...

Glomus tumors treated with stereotactic radiosurgery: A retrospective study.

BACKGROUND: Glomus tumors are difficult to manage surgically because they are vascular tumors that are topographically associated with important vascu...

Stereotactic robot-assisted MRI-guided laser thermal ablation of radiation necrosis in the posterior cranial fossa: technical note.

Laser interstitial thermal therapy (LITT) is a minimally invasive procedure used to treat a variety of intracranial lesions. Utilization of robotic as...

Comparison of Re-irradiation Outcomes for Charged Particle Radiotherapy and Robotic Stereotactic Radiotherapy Using CyberKnife for Recurrent Head and Neck Cancers: A Multi-institutional Matched-cohort Analysis.

AIM: To compare survival outcomes for charged particle radiotherapy (CP) and stereotactic body radiotherapy using CyberKnife (CK) in patients who had ...