Tucker Netherton

Cost-effective immobilization for whole brain radiation therapy.

Normal tissue doses from MV image-guided radiation therapy (IGRT) using orthogonal MV and MV-CBCT.

Interplay effect on a 6-MV Flattening-Filter-Free linear accelerator with high dose rate and fast multi-leaf collimator motion treating breast and lung phantoms.

Independent validation of machine performance check for the Halcyon and TrueBeam linacs for daily quality assurance.

Varian Halcyon dosimetric comparison for multiarc VMAT prostate and head-and-neck cancers.

A snapshot of medical physics practice patterns.

Dosimetric impact and detectability of multi-leaf collimator positioning errors on Varian Halcyon.

Acceptance and verification of the Halcyon-Eclipse linear accelerator-treatment planning system without 3D water scanning system.

Automatic contouring system for cervical cancer using convolutional neural networks.

The Emergence of Artificial Intelligence within Radiation Oncology Treatment Planning.

Evaluation of a multiview architecture for automatic vertebral labeling of palliative radiotherapy simulation CT images.

Development and dosimetric assessment of an automatic dental artifact classification tool to guide artifact management techniques in a fully automated treatment planning workflow.

Beam energy metrics for the acceptance and quality assurance of Halcyon linear accelerator.

Technical Note: Dose prediction for head and neck radiotherapy using a three-dimensional dense dilated U-net architecture.

VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images.

Body region-specific 3D age-scaling functions for scaling whole-body computed tomography anatomy for pediatric late effects studies.

An Automated Treatment Planning Framework for Spinal Radiation Therapy and Vertebral-Level Second Check.

Clinical acceptability of fully automated external beam radiotherapy for cervical cancer with three different beam delivery techniques.

OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines.

Multi-organ segmentation of abdominal structures from non-contrast and contrast enhanced CT images.

Customizable landmark-based field aperture design for automated whole-brain radiotherapy treatment planning.

Automating the treatment planning process for 3D-conformal pediatric craniospinal irradiation therapy.

Outcomes of Complex Abdominal Wall Reconstruction After Oncologic Resection: 14-Year Experience at an NCI-Designated Cancer Center.

Deep Learning-Based Dose Prediction for Automated, Individualized Quality Assurance of Head and Neck Radiation Therapy Plans.

ASO Visual Abstract: Outcomes of Complex Abdominal Wall Reconstruction After Oncologic Resection: 14-Year Experience at an NCI-Designated Cancer Center.

Automated Contouring and Planning in Radiation Therapy: What Is 'Clinically Acceptable'?

Commissioning and dosimetric validation of a novel compensator-based Co-60 IMRT system for evaluating suitability to automated treatment planning.

A deep-learning-based dose verification tool utilizing fluence maps for a cobalt-60 compensator-based intensity-modulated radiation therapy system.

Addressing the Global Expertise Gap in Radiation Oncology: The Radiation Planning Assistant.

Identifying the optimal deep learning architecture and parameters for automatic beam aperture definition in 3D radiotherapy.

Deep learning-based dose prediction to improve the plan quality of volumetric modulated arc therapy for gynecologic cancers.

Automated contouring and statistical process control for plan quality in a breast clinical trial.

A real-time contouring feedback tool for consensus-based contour training.