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Results for "challenge multi": 27 found

Addressing Missing MRI Sequences: A DL-Based Region-Focused Multi-Sequence Framework for Synthetic Image Generation

Authors: Amir Abdollahi, Oliver Jäkel, Maxmillian Knoll, Rakshana Murugan, Adithya Raman, Patrick Salome

Affiliation: UKHD & DKFZ, Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), German Cancer Research Centre(DKFZ), DKFZ, MGH

Abstract Preview: Purpose:
Missing MRI sequences, due to technical issues in data handling or clinical constraints like contrast agent intolerance, limit the use of medical imaging datasets in computational analysis...

Advancing Magnetic Resonance Imaging (MRI) Safety Clearance: Utilizing Dual-Energy CT (DECT) Material Decomposition for Foreign Object Assessment

Authors: Anzi Zhao

Affiliation: Northwestern Medicine

Abstract Preview: Purpose: This study investigates the utility of Dual-Energy Computed Tomography (DECT) material decomposition in resolving Magnetic Resonance Imaging (MRI) safety concerns for patients with unidentifi...

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...

BEST IN PHYSICS MULTI-DISCIPLINARY: Foundation Model-Empowered Unsupervised 3D Deformable Medical Image Registration

Authors: Xianjin Dai, PhD, Zhuoran Jiang, Lei Ren, Lei Xing, Zhendong Zhang

Affiliation: University of Maryland School of Medicine, Department of Radiation Oncology, Stanford University, Duke University, Stanford University

Abstract Preview: Purpose: Unsupervised deep learning has shown great promise in deformable image registration (DIR). These methods update model weights to optimize image similarity without necessitating ground truth d...

Decreasing the Dependence of CT Number on the Position in the Field-of-View Using Photon Counting Detector CT

Authors: Yanle Hu, Shuai Leng, Cynthia H. McCollough, Maryam Sadeghian, Joe Swicklik

Affiliation: Mayo Clinic Arizona, Mayo Clinic

Abstract Preview: Purpose: The dependence of CT number on position in the field-of-view (FOV) imposes challenges in radiotherapy treatment planning. This study aims to decrease this dependence using photon counting det...

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...

Denoising Diffusion-Weighted Images of Rectal Cancer Acquired on a 0.35 T Magnetic Resonance Imaging-Guided Linear Accelerator Using Singular Value Decomposition

Authors: Jacqueline M. Andreozzi, Tess Armstrong, Shiva Bhandari, John M Bryant, Jessica M Frakes, David J. Gladstone, Sarah E Hoffe, Kujtim Latifi, Arash Naghavi, Steven Nichols, Ibrahim M. Oraiqat, Russell Palm, Gage H. Redler, Stephen A Rosenberg, Joseph Weygand

Affiliation: Department of Radiation Oncology and Applied Science, Dartmouth Health, Thayer School of Engineering, Dartmouth College, Department of Radiation Oncology, Ohio State University, Moffitt Cancer Center, Department of Radiation Oncology, Moffitt Cancer Center

Abstract Preview: Purpose: The MR-linac provides unique opportunities for integrating advanced imaging into radiotherapy workflows, but the lower sensitivity of systems like the 0.35T model can pose challenges for diff...

Development and Validation of Novel Two-Stage Vascular Segmentation Model for Interventional Angiography

Authors: Abid Khan, Chad Klochko, Michael J Kovalchick, Hyeok Jun Lee, Hani Nasr, Krishnan Shyamkumar, Kundan S Thind

Affiliation: Henry Ford Radiology, Wayne State University, Henry Ford Health, HFHS

Abstract Preview: Purpose: Automated vascular segmentation in interventional angiography is challenged by contrast kinetics, vessel variations, and 2D projections, limiting the effectiveness of single-model approaches....

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...

Dosinme: A 3D Visualization Platform for Internal Dosimetry and Radionuclide Behavior in Computational Human Phantoms

Authors: Lotem Buchbinder Shadur, Shaheen Dewji, Martin Graffigna, Alejandro Rafael Martinez, Emmanuel Mate-Kole, Antonio McClain, Samuel Taylor, Jeffrey Wang

Affiliation: Student, Nuclear and Radiological Engineering and Medical Physics Programs, Georgia Institute of Technology

Abstract Preview: Purpose: DosInMe is an internal dosimetry visualization tool developed by the Radiological Engineering, Detection, and Dosimetry Laboratory at Georgia Tech to assist researchers and professionals in v...

First Phantom Testing of Biology-Guided Radiotherapy for Sequential Integrated Boost Radiotherapy

Authors: Girish Bal, David J. Carlson, Huixiao Chen, Zhe (Jay) Chen, Emily A. Draeger, Dae Yup Han, Henry S. Park

Affiliation: RefleXion Medical, Department of Therapeutic Radiology, Yale University School of Medicine

Abstract Preview: Purpose: This study explores the feasibility, accuracy, and dosimetric performance of hybrid biology-guided radiotherapy (BgRT) combined with image-guided radiotherapy (IGRT) for delivering sequential...

Fully Automated Review of Prostate Radiotherapy Treatment Plan Quality

Authors: Yasin Abdulkadir, John Charters, Melissa Ghafarian, James M. Lamb, Dishane Chand Luximon, Jack Neylon

Affiliation: Department of Radiation Oncology, University of California, Los Angeles

Abstract Preview: Purpose:
Assessment of radiotherapy treatment quality in large-scale multi-institutional contexts remains an outstanding challenge. Retrospective human review of treatment plans is labor intensive ...

High-Temporal Dynamic CBCT Imaging Via Gaussian Neural Representation

Authors: Weixing Cai, Laura I. Cervino, Yabo Fu, Licheng Kuo, Tianfang Li, Xiang Li, Jean M. Moran, Huiqiao Xie, Hao Zhang

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: This study introduces a novel spatiotemporal Gaussian neural representation framework to reconstruct high-temporal dynamic CBCT images from 1-minute acquisition, preserving motion dynamics an...

Improvement of Spine Phantom for MR Imaging of the Spine

Authors: Richard Dortch, Thammathida Ketsiri, Zhiqiang Li, Shiv P. Srivastava

Affiliation: Barrow Neurological Institute, Dignity Health Cancer Institute, St. Joseph's Hospital & Medical Center

Abstract Preview: Purpose: Imaging the spinal cord post-surgery is challenging due to metal surgical implants, which induce signal loss and geometric distortions. Together, this hinders the visualization of the spinal ...

Improving Mammography Diagnosis Accuracy through Global Context and Local Lesion Integration

Authors: Minbin Chen, Xiaoyi Dai, Xiaoyu Duan, Chunhao Wang, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Rihui Zhang

Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: Deep learning (DL)-based mammography diagnosis presents unique challenges, as accurate interpretation requires both global breast condition analysis and local lesion structural information. E...

Integrating SPECT and Compton Imaging for Multi-Energy Photon Reconstruction

Authors: Qihui Lyu, Javier Caravaca Rodriguez, Youngho Seo, Ke Sheng, Jingjie Yu

Affiliation: University of California San Francisco, University of California, San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose:
Simultaneous broad-energy imaging is critical for many theragnostic applications, but the current Single-Photon Emission Computed Tomography (SPECT) can only image low energy photons with ...

Latent Diffusion Model-Driven Semi-Supervised Semantic Segmentation of Cell Nuclei

Authors: Mark Anastasio, Hua Li, Zhuchen Shao

Affiliation: Washington University School of Medicine, University of Illinois Urbana-Champaign

Abstract Preview: Purpose: Automated semantic segmentation of cell nuclei in microscopic images is vital for disease diagnosis and tissue microenvironment analysis. However, obtaining large annotated datasets for train...

Memory-Efficient Deep Learning for Volumetric Cone-Beam CT Image Reconstruction

Authors: Ziqi Gao, Lei Xing, Siqi Ye, S. Kevin Zhou

Affiliation: Department of Radiation Oncology, Stanford University, University of Science and Technology of China (USTC)

Abstract Preview: Purpose: To address the challenge of high memory usage in volumetric cone-beam CT (CBCT) imaging, we propose a method that combines joint reconstruction and super-resolution for sparsely sampled CBCT ...

Monte Carlo Simulation of Surface Radiation Dose for Cherenkov Imaging: Comparison with Commissioning Data for Truebeam and Halcyon

Authors: Hongjing Sun, Weibing Yang, Timothy C. Zhu, Yifeng Zhu

Affiliation: University of Pennsylvania

Abstract Preview: Purpose: This study aims to compare the commissioning results of TrueBeam and Halcyon linear accelerators with Monte Carlo (MC) simulations conducted using TOPAS. The ultimate goal is to leverage MC s...

Multi-Scale, Multi-Task Framework with Jacobian Descent for Multi-Plan Dose Prediction in Sequential Boost Radiotherapy

Authors: Steve B. Jiang, Mu-Han Lin, Yu-Chen Lin, Austen Matthew Maniscalco, Dan Nguyen, David Sher, Xinran Zhong

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, UT Southwestern Medical Center, UT Dallas

Abstract Preview: Purpose:
Sequential boost radiotherapy (RT) poses a challenge in allocating dose across multiple plans while protecting organs at risk (OARs). Clinicians must decide whether OAR sparing should occu...

NA-Unetr: A Neighborhood Attention Transformer Network for Enhanced 3D Segmentation of the Left Anterior Descending Artery

Authors: Hassan Bagher-Ebadian, Ahmed I Ghanem, Joshua P. Kim, Chengyin Li, Rafi Ibn Sultan, Kundan S Thind, Dongxiao Zhu

Affiliation: Wayne State University, Department of Radiation Oncology, Henry Ford Health-Cancer, Detroit, MI and Alexandria Department of Clinical Oncology, Faculty of Medicine, Alexandria University, Henry Ford Health

Abstract Preview: Purpose: Accurate segmentation of the Left Anterior Descending (LAD) artery in free-breathing 3D treatment planning CT is crucial for radiotherapy but remains challenging due to its small size, comple...

Off- Axis Winston Lutz on C-Arm Linac Using in-House Phantom

Authors: Colton Baley, Bhuvaneswari Narayanan, Niko Papanikolaou, Daniel L. Saenz

Affiliation: UT Health San Antonio, Texas Oncology, University of Texas HSC San Antonio

Abstract Preview: Purpose: To evaluate the accuracy of off-axis winston lutz (WLT) for linac based stereotactic radiosurgery (SRS) treatments using in-house phantom.

Methods: Traditional WLT that uses cone and s...

Redefining the Down-Sampling Scheme of U-Net for Precision Biomedical Image Segmentation

Authors: Yizheng Chen, Md Tauhidul Islam, Mingjie Li, Lei Xing

Affiliation: Department of Radiation Oncology, Stanford University

Abstract Preview: Purpose:
Biomedical image segmentation (BIS) is a cornerstone of medical physics, enabling accurate delineation of anatomical structures and abnormalities, which is critical for diagnosis, treatmen...

Research on Multi-Organ Segmentation Based on Cross-Domain Transfer Learning

Authors: Jiali Gong, Yi Guo, Chi Han, Wanli Huo, Hongdong Liu, Zhao Peng, Yaping Qi, Zhaojuan Zhang

Affiliation: Department of Radiotherapy, cancer center, The First Affiliated Hospital of Fujian Medical University, Department of Oncology, Xiangya Hospital, Central South University, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, China Jiliang University, Division of lonizing Radiation Metrology, National Institute of Metrology, Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University

Abstract Preview: Purpose: To address overfitting from limited training data in multi-organ segmentation, an efficient transfer learning framework is proposed. It reduces reliance on training samples, enabling a single...

Tackling the Challenge of Multi-Target Metastases Treatment: Evaluation of Ethos Treatment Planning System

Authors: Avery Antes, Bulent Aydogan, Rama Chicfeh, Erik Pearson, Neslihan Sarigul

Affiliation: The University Of Chicago, The University of Chicago

Abstract Preview: Purpose: This study evaluates the performance of the Ethos Treatment Planning System (TPS) in managing oligometastatic cancer patients previously treated using multiple isocenter plans.
Methods: Th...

Using Multi-Peak Reconstructions for Dosimetry of Fast and Quantitative Lutetium-177 SPECT/CT

Authors: Julia Brosch-Lenz, Munir Ghesani, Francesc Massanes, Michael Morris, Babak Saboury, Eliot Siegel, Alexander Hans Vija

Affiliation: Institute of Nuclear Medicine, Siemens Medical Solutions USA Inc., Molecular Imaging

Abstract Preview: Purpose: Quantitative imaging of the radiopharmaceutical distribution is crucial for treatment evaluation and dosimetry. However, as patient numbers for Lutetium-177-(177Lu)-labelled therapies continu...

Using Open-Source Reasoning Large Language Models for Radiotherapy Structure Name Harmonization

Authors: Claus Belka, Stefanie Corradini, Christopher Kurz, Guillaume Landry, Matteo Maspero, Adrian Thummerer, Erik van der Bijl

Affiliation: Department of Radiation Oncology, LMU University Hospital, LMU Munich, Radboud University Medical Center, UMC Utrecht

Abstract Preview: Purpose: To automatically harmonize non-standardized organ-at-risk (OAR) structure names from multi-lingual, multi-institutional radiotherapy datasets using state-of-the-art open-source reasoning larg...