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Results for "generating brain": 18 found

A Ground Truth Label-Mediated Method for Improved Bone and Gas Cavity Definition for MRI-Guided Online Adaptive Radiotherapy Workflows Using Synthetic CT Images.

Authors: Benito De Celis Alonso, Braian Adair Maldonado Luna, Gerardo Uriel Perez Rojas, René Eduardo Rodríguez-Pérez, Kamal Singhrao

Affiliation: Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute, Harvard Medical School, Faculty of Physics and Mathematics, Benemérita Universidad Autónoma de Puebla

Abstract Preview: Purpose: Artificial Intelligence (AI)-generated synthetic CT (sCT) images can be used to provide electron densities for dose calculation for online adaptive MRI-guided stereotactic body radiotherapy (...

AI-Driven Troubleshooting for Truebeam Systems: Development and Testing of a Gpt-4o Chatbot

Authors: Sean P. Devan, Cory S. Knill, Charles K. Matrosic, Zheng Zhang

Affiliation: University of Michigan

Abstract Preview: Purpose: Physicists troubleshooting machine issues during patient treatments often face high-pressure situations, balancing error codes, resource constraints, and time-sensitive decisions. To streamli...

An Agglomerative Clustering-Based Program for Optimizing Multiple-Target SRS Treatment Planning

Authors: Josephine Chen, CheukKai Becket Hui, Yildirim D. Mutaf

Affiliation: Kaiser Permanente

Abstract Preview: Purpose:
To demonstrate the effectiveness of a target clustering program in generating cluster configurations and isocenter placements for multiple brain lesions in SRS treatment planning, with the...

Automated Treatment Planning for Linac-Based Stereotactic Radiosurgery of Intraocular Malignancies Via Hyperarc Knowledge-Based Planning

Authors: Chase Cochran, Shane McCarthy, Damodar Pokhrel, William St Clair

Affiliation: University of Kentucky, Department of Radiation Medicine, University of Kentucky, Radiation Medicine

Abstract Preview: Purpose: Manually generating intraocular stereotactic radiosurgery (SRS) plans involves significant challenges, including lengthy planning times and inter-planner variability. Knowledge-based SRS plan...

Big Data in-Vivo Epid Image Prediction for VMAT Radiotherapy

Authors: Casey E. Bojechko, Lance C Moore

Affiliation: University of California, San Diego, University of California San Diego

Abstract Preview: Purpose: EPID images collected during treatment can serve as an in-vivo error detection mechanism. Previous works have shown that comparing in-vivo EPID images to AI-predicted EPID images for IMRT pla...

Biologically Guided Deep Learning for MRI-Based Brain Metastasis Outcome Prediction after Stereotactic Radiosurgery

Authors: Evan Calabrese, Hangjie Ji, Kyle J. Lafata, Casey Y. Lee, Eugene Vaios, Chunhao Wang, Lana Wang, Zhenyu Yang, Jingtong Zhao

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Duke Kunshan University, North Carolina State University

Abstract Preview: Purpose: To develop a biologically guided deep learning (DL) model for predicting brain metastasis(BM) local control outcomes following stereotactic radiosurgery (SRS). By integrating pre-SRS MR image...

Clinical Validation of Fully Automated Script for Plan Conversion between Linacs with Different Mlc Model

Authors: David L. Barbee, Paulina E. Galavis, Lena Adel Samad, Jose R. Teruel Antolin

Affiliation: NYU, NYU Langone Health

Abstract Preview: Purpose: To validate an automated script that converts treatment plans of varying Varian MLC models

Methods: A C# script was developed using the Eclipse Scripting API to convert treatment plans...

Design and Testing of a Portable Microwave Scanner for Imaging Soft Tissue and Tumors in Cancer Patients

Authors: Imad M. Ali, Nesreen Alsbou, Sakeeneh Majeed

Affiliation: University of Central Oklahoma, University of Oklahoma Health Sciences Center

Abstract Preview: Purpose: to design and assess a microwave imaging system equipped with multiple antennas for generating high-resolution 3D images of phantom models that simulate abdominal, thoracic, and brain tissues...

Development of a Deep Learning Model for Accurate Brain Dose Prediction in Multi-Target Stereotactic Radiosurgery Plan Evaluation

Authors: Wenchao Cao, Yingxuan Chen, Haisong Liu, Wenyin Shi, Wentao Wang, Lydia J. Wilson, Zhenghao Xiao

Affiliation: Thomas Jefferson University

Abstract Preview: Purpose: Multi-target stereotactic radiosurgery (SRS) planning poses challenges due to complex geometries, small target volumes, and steep dose gradients. Achieving a balance between target coverage a...

Evaluation of the Inverse Planning Optimization with Leksell Gammaplan®

Authors: Nina Burbure, Tawfik G. Giaddui, Shidong Li, Curtis Miyamoto, Jeremy Price, Bin Wang

Affiliation: FCCC at Temple University Hospital

Abstract Preview: Purpose: Our GammaKnife(GK) has been upgraded from 4C to ICON recently. In this study we evaluated the performance of Lightning IPO for ICON.
Methods: 10 cases with single brain metastasis previous...

Generating 3D Brain in Volume (BRAVO) Images Using Attention-Gated Conditional Gan (AGC-GAN)

Authors: Nan Li, Shouping Xu, Gaolong Zhang, Xuerong Zhang

Affiliation: Department of Radiation Oncology, HeBei YiZhou proton center, School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose:
The 3D BRAVO sequence is an advanced magnetic resonance (MR) technique that allows for image reconstruction at any angle. It offers 1 mm gapless scanning and has a high signal-to-noise rat...

Generating Brain Pseudo-CT from PET-Only Images Using Deep Learning Method

Authors: Pouya Azarbar, Nima Kasraie, Mahsa Shahrbabki Mofrad, Peyman Sheikhzadeh

Affiliation: UT Southwestern Medical Center, Shahid Beheshti University of Medical science, Imam Khomeini Hospital Complex,Tehran University of Medical Sciences, Tehran University of Medical Science

Abstract Preview: Purpose: PET imaging become crucial in diagnosing and managing various diseases, but its key limitation is the lack of detailed anatomical information. Integrating CT-scans with PET images enhances cl...

Generation of Virtual Lung PET Images from CT Data Via Deep Learning for Accelerated Tumor Detection and Preliminary Diagnosis

Authors: Pouya Azarbar, Nima Kasraie, Peyman Sheikhzadeh

Affiliation: UT Southwestern Medical Center, Shahid Beheshti University of Medical science, Imam Khomeini Hospital Complex,Tehran University of Medical Sciences

Abstract Preview: Purpose: Positron Emission Tomography (PET) is crucial for diagnosing and monitoring diseases due to its functional imaging capabilities. However, its high cost, significant radiation exposure, and li...

Human-like Deep Learning-Based Whole-Brain Radiotherapy Treatment Planning

Authors: Adnan Jafar, Xun Jia, An Qin

Affiliation: Johns Hopkins University

Abstract Preview: Purpose: 3D whole-brain radiotherapy (WBRT) is widely used due to its simplicity and effectiveness. While modern treatment planning systems, like RayStation, offer automated Field-in-Field planning, p...

Mask-Based Synthetic Contrast-Enhanced CT Generation for Advancing Data Limited Segmentation on Cardiac Substructure

Authors: Jin Sung Kim, Chanwoong Lee, Young Hun Yoon

Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine

Abstract Preview: Purpose: Chest contrast-enhanced CT (CECT) serves as a valuable tool for cardiac imaging, but its lack of detailed anatomical visualization limits its utility in segmentation tasks. While CECT offers ...

Posterior-Mean Diffusion Model for Realistic PET Image Reconstruction

Authors: Osama R. Mawlawi, Yiran Sun

Affiliation: RICE University, UT MD Anderson Cancer Center

Abstract Preview: Purpose: Conventional PET reconstruction methods often produce noisy images with artifacts due to data/model mismatches and inconsistencies. Recently, deep learning-based conditional denoising diffusi...

Streamlining Hippocampal-Sparing Whole-Brain VMAT Planning: Enhancing Efficiency and Plan Quality with an Automated Workflow

Authors: Eric C. Ford, Yulun He, Minsun Kim, Dustin Melancon, Juergen Meyer, Dong Joo Rhee, Yinghua Tao

Affiliation: Department of Radiation Oncology, Fred Hutchinson Cancer Center, University of Washington, MD Anderson Cancer Center, University of Washington

Abstract Preview: Purpose: To develop and evaluate an automated-planning technique capable of generating high-quality treatment plans for hippocampal-sparing-whole-brain radiation therapy.
Methods: An auto-planning ...

The Development of a Novel Biomechanical Model for Accurate Contour Deformation during Online Adaptative Metastatic Bone Cancer Radiotherapy Planning.

Authors: Jeremy S. Bredfeldt, Benito De Celis Alonso, Braian Adair Maldonado Luna, Kevin M. Moerman, Gerardo Uriel Perez Rojas, René Eduardo Rodríguez-Pérez, Kamal Singhrao

Affiliation: Department of Radiation Oncology, Brigham and Women's Hospital, Harvard Medical School, Department of Radiation Oncology, Brigham and Women's Hospital, Dana Farber Cancer Institute, Harvard Medical School, Department of Mechanical Engineering, University of Galway, Faculty of Physics and Mathematics, Benemérita Universidad Autónoma de Puebla

Abstract Preview: Purpose: Online adaptive radiotherapy replanning for single-isocenter bone cancer metastasis treatment reduces on-table treatment time and patient discomfort compared to the multi-isocenter standard-o...