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Results for "Junghoon Lee": 9 found

A Python Package for GPU-Accelerated Photon Dose Calculation for Advanced and Generalizable Auto-Planning Approaches: Validation for Multiple Linear Accelerator Vendors and Institutions

Authors: Jaryd Ricardo Christie, Anthony J. Doemer, William T. Hrinivich, Junghoon Lee, Calin Reamy, Kundan S Thind

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Johns Hopkins University, Henry Ford Health

Abstract Preview: Purpose: To develop and validate an open-source Python package for fast, widely compatible, and user-friendly photon dose calculation algorithm through comparisons with clinical treatment planning sys...

Automatic Tumor Segmentation and Catheter Detection from MRI for Cervical Cancer Brachytherapy Using Uncertainty-Aware Dual Convolution-Transformer Unet

Authors: Majd Antaki, Rohini Bhatia, Gayoung Kim, Yosef Landman, Junghoon Lee, Akila N. Viswanathan

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Physics and Advanced Development Elekta

Abstract Preview: Purpose: Brachytherapy is a standard radiation therapy approach for cervical cancer, which directly delivers radiation source to the tumor using catheters. Treatment planning requires identification o...

BEST IN PHYSICS IMAGING: Population-Based Cardio-Respiratory Motion Model to Simulate 4D CT Angiography and 2D+t Fluoroscopy for Percutaneous Coronary Intervention

Authors: Debarghya China, Junghoon Lee, Ali Uneri

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University, Johns Hopkins Univ

Abstract Preview: Purpose: This study aims to develop a population-based cardio-respiratory motion model and apply it to patient-specific 3D CTA to simulate 4D CTA and 2D+t fluoroscopy sequences. The developed motion m...

Brain Tumor Segmentation from Multi-Parametric MRI with Integrated Evidential Uncertainty Estimation

Authors: Sahaja Acharya, Matthew Ladra, Junghoon Lee, Lina Mekki

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University

Abstract Preview: Purpose: Multi-parametric MRI (mpMRI) is widely used for deep learning (DL)-based automatic segmentation of brain tumors. While multi-contrast images concatenated as channels are typically input to ne...

Cerebellar Mutism Syndrome Prediction with 3D Residual Convolutional Neural Network

Authors: Sahaja Acharya, Matthew Ladra, Junghoon Lee, Lina Mekki, Bohua Wan

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University, Department of Computer Science, Johns Hopkins University

Abstract Preview: Purpose: Cerebellar mutism syndrome (CMS) is the most frequently observed complication in children undergoing surgical resection of posterior fossa tumors. Previous work explored lesion to symptom map...

Deep Learning Based Automatic Cerebrovascular Segmentation in Multi-Center TOF-MRA Datasets

Authors: Gayoung Kim, Junghoon Lee

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University

Abstract Preview: Purpose: 3D time-of-flight magnetic resonance angiography (TOF-MRA) is widely used for visualizing cerebrovascular structures. Accurate segmentation of cerebrovascular structures is critical for relia...

Explainable Xerostomia Prediction with Decoupled High Resolution Class Activation Map

Authors: Junghoon Lee, Todd R. McNutt, Harry Quon, Bohua Wan

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Johns Hopkins University, Department of Computer Science, Johns Hopkins University

Abstract Preview: Purpose: Xerostomia is a common toxicity in head and neck cancer (HNC) radiotherapy (RT). A few deep learning (DL) models have been proposed to predict the chance of xerostomia 12 months after RT with...

Frequent MR Imaging of Fibrosis during Radiation Therapy: Implications for Adaptive RT in Gynecologic Cancer

Authors: Himanshu Bhat, Bruce Lewis Daniel, Junghoon Lee, Michael B. Roumeliotis, Ehud J. Schmidt, Ravi Seethamraju, Khadija Sheikh, Pan Su, Akila N. Viswanathan

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Siemens Medical Solutions USA Inc., Stanford Medical School, Department of Cardiology, Johns Hopkins University

Abstract Preview: Purpose: To perform frequent MRI during EBRT and brachytherapy (BT) to evaluate RT-induced fibrosis and remnant tumor changes, identified using ultrashort echo-time (UTE) and multiparametric (mpMRI), ...

Reinforcement Learning Based Machine Parameter Optimization for Two-Arc Prostate VMAT Planning

Authors: William T. Hrinivich, Junghoon Lee, Lina Mekki

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University, Johns Hopkins University

Abstract Preview: Purpose: Volumetric modulated arc therapy (VMAT) planning is a computationally expensive process. In this work, we propose a reinforcement learning (RL) framework to automatically optimize dose rate a...