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Results for "dual decoder": 5 found

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...

Deep-Learning Based Spectral Artifact Removal with In Vivo 7T Proton MRSI Data

Authors: Anke Henning, Mahrshi Jani, Tianyu Wang, Andrew Wright, Xinyu Zhang

Affiliation: Advanced Imaging Research Center (AIRC), UT Southwestern Medical Center

Abstract Preview: Purpose: Proton MRSI offers critical metabolic insights into diseased brain processes but is prone to artifacts, and current post-processing methods are often insufficient, resulting in low-quality da...

Integrating Multiple Modalities with Pretrained Swin Foundation Model for Head and Neck Tumor Segmentation

Authors: Jue Jiang, Aneesh Rangnekar, Shiqin Tan, Harini Veeraraghavan

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Weill Cornell Graduate School of Medical Sciences

Abstract Preview: Purpose: Clinicians often use information from FDG-PET and CT to interpret and delineate gross tumor (GTVp) and nodal (GTVn) volumes for radiotherapy planning in head and neck (HN) cancer patients. He...

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...

Simultaneous Synthesis of Lung Perfusion and Ventilation Images from CT Using a Dual-Decoder Residual Attention Network for Lung Disease Diagnosis

Authors: Li-Sheng Geng, David Huang, Haoze Li, Xi Liu, Meng Wang, Tianyu Xiong, Ruijie Yang, Weifang Zhang, Meixin Zhao

Affiliation: School of Physics, Beihang University, Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Department of Radiation Oncology, Peking University Third Hospital, Department of Nuclear Medicine, Peking University Third Hospital, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: This study aimed to develop a deep learning-based framework for simultaneously generating lung perfusion and ventilation images from three-dimensional computed tomography (3D CT) images.
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