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Results for "multi score": 38 found

A Multi-Institutional Survey of Current Therapeutic Medical Physics Residents’ Satisfaction and Interview Experience

Authors: Seifallah Emam, Gilberto Gonzalez, Anna E. Rodrigues

Affiliation: Duke University, University of Oklahoma Health Sciences Center

Abstract Preview: Purpose:
To survey current therapeutic medical physics residents on 1) the accuracy with which residency programs were represented during interviews, 2) factors that most strongly impacted resident...

A Multi-Regional and Multi-Omics Approach to Predict Penumonitis in Patients with Locally Advanced Non-Small Cell Lung Cancer in Nrg Oncology Trial RTOG 0617

Authors: Katelyn M. Atkins, Indrin J. Chetty, Elizabeth M. McKenzie, Taman Upadhaya, Samuel C. Zhang

Affiliation: Department of Radiation Oncology,Cedars-Sinai Medical Center, Cedars-Sinai Medical Center

Abstract Preview: Purpose:
We explored a multi-regional and multi-omics approach to extract CT-based radiomics and 3D dosiomics features to predict radiation pneumonitis (RP) in patients with locally advanced Non-Sm...

An Automated Tool for the Categorization of a Clinical Database By Anatomic Region for Big Data Applications

Authors: Yasin Abdulkadir, Justin Hink, James M. Lamb, Jack Neylon

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

Abstract Preview: Purpose: Curation remains a significant barrier to the use of ‘big data’ radiotherapy planning databases of 100,000 patients or more. Anatomic site of treatment is an important stratification for almo...

An International Multi-Institutional Espresso Study of Developing the Specialized-Equipment-Free Remote Audit for Single-Isocenter Multi-Target Stereotactic Radiosurgery

Authors: Juan-Francisco Calvo-Ortega, Andrew Cousins, Ashley Cullen, Andrew Dipulia, Peter B. Greer, Seng Boh Gary Lim, Shih-Chi Lin, D. Michael Lovelock, Conor McGarry, Victoria Robinson, Cameron Stanton, Baozhou Sun, Ching-Ling Teng, Gemma Warner, Benjamin J. Zwan

Affiliation: Northern Ireland Cancer Centre, Baylor College of Medicine, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Christchurch Hospital, Northwell, Central Coast Cancer Centre, Calvary Mater Hospital, Hospital Quironsalud Barcelona, Icahn School of Medicine at Mount Sinai, Chris O'Brien Lifehouse, University of Newcastle

Abstract Preview: Purpose: This multi-institution Electronic Silicon-based Remote Survey of Small-field Output (ESPRESSO) study aims to develop the remote audit process to evaluate the safety of single-isocenter multi-...

BEST IN PHYSICS MULTI-DISCIPLINARY: Building a Cross-Modality Model to Integrate Bio-Clinical Features, Anatomical MRI, and White-Matter Pathlength Mapping for Personalized Glioblastoma RT Planning

Authors: Steve Braunstein, Angela Jakary, Hui Lin, Bo Liu, Janine Lupo, Tiffany Ngan, Ke Sheng, Nate Tran

Affiliation: Radiation Oncology, University of California San Francisco, Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, University of California San Francisco, Department of Radiology and Biomedical Imaging, University of California San Francisco, Department of Radiation Oncology, University of California, San Francisco

Abstract Preview: Purpose: Current RT clinical target volumes (CTVs) for Glioblastoma (GBM) employ 2cm isotropic expansions of gross tumor volumes. However, studies showed patients still experience progression beyond t...

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...

Brachyplancheck: An Independent Monte Carlo Dose Calculation Tool for Brachytherapy Using Egs_Brachy

Authors: Amy Tien Yee Chang, Chi Wai Cheung, Tin Lok Chiu, Chen-Yu Huang, Chi Wa Kong, Pei-Xiong Li, Pak Hang Nam, Bin Yang, Siu Ki Yu

Affiliation: Comprehensive Oncology Centre, Hong Kong Sanatorium and Hospital, Medical Physics Department, Hong Kong Sanatorium and Hospital

Abstract Preview: Purpose: This study introduces BrachyPlanCheck, an independent Monte Carlo (MC)-based dose calculation tool for 192Ir brachytherapy retrospective study or algorithm commissioning.
Methods: BrachyPl...

Characterization of Linear Energy Transfer Spectra in Mini Beam Spatially Fractionated Proton Therapy

Authors: Serdar Charyyev, Kaan Dere, Edgar Gelover, Mohammad Khurram Khan, Liyong Lin, Mark McDonald, Cristina Oancea, Alexander Stanforth, Sibo Tian, Suk Whan (Paul) Yoon, Mingyao Zhu

Affiliation: Department of Radiation Oncology, Stanford University, Stanford University, Emory University, Department of Radiation Oncology and Winship Cancer Institute, Emory University, Advacam

Abstract Preview: Purpose: The conventional implementation of proton spatially fractionated radiotherapy (SFRT) utilizes physical collimators with apertures to generate minibeams, creating alternating regions of high-d...

Combining Proton Flash and Spatially Fractionated Radiotherapy – Experimental and Simulation Based Dosimetric Characterization

Authors: Gulakhshan M Hamad, Sina Mossahebi, Yannick P. Poirier, Amit Sawant

Affiliation: University of Maryland School of Medicine, Maryland University Baltimore

Abstract Preview: Purpose:
The combination of ultra-high dose rate (UHDR) proton therapy, known for normal tissue sparing, with spatially-fractionated radiotherapy (SFRT), promising enhanced tumor control and tissue...

Comprehensive Analysis of Plan Modulation in SRS/SBRT Plans: A Single Institution Study of 461 Cases

Authors: Yunfeng Cui, Will Giles, Xinyi Li, Ke Lu, Jennifer C. O'Daniel, Anna E. Rodrigues, Chunhao Wang, Lana Wang, Yibo Xie, Sua Yoo, Jingtong Zhao

Affiliation: Duke University, Duke University Medical Center

Abstract Preview: Purpose:
To establish quantitative measurement of plan modulation for SRS/SBRT treated with Volumetric Modulated Arc Therapy (VMAT) on C-arm LINACs.
Methods:
A total of 461 plans were analyze...

Cycle-Consistent Multi-Task Automated Segmentation and Synthetic CT Generation Model for Adaptive Proton Therapy

Authors: Derek Tang, Susu Yan

Affiliation: Massachusetts General Hospital

Abstract Preview: Purpose: To evaluate the performance of a multi-task automated-segmentation and synthetic CT generation model (sCT) and investigate its application in an adaptive proton therapy workflow.
Methods: ...

Demystifying Magnetic Resonance Imaging: Targeted Educational Initiatives for Medical Physicists in Türkiye and Preclinical Medical Students in the United States

Authors: Samuel A. Einstein, Jesutofunmi Fajemisin, Evren O. Göksel, Görkem O. Güngör, Marthony Robins, Travis C. Salzillo, Charles R. Thomas, Turgay Toksay, Joseph Weygand, Yue Yan

Affiliation: Acibadem MAA University, Department of Radiation Oncology and Applied Science, Dartmouth Health, Dartmouth College, Moffitt Cancer Center, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Penn State College of Medicine, Bursa Ali Osman Sönmez Oncology Hospital

Abstract Preview: Purpose: Magnetic resonance imaging (MRI) is an indispensable clinical tool, offering unparalleled soft tissue contrast critical for diagnosing and managing a wide range of conditions. However, its co...

Developing a Comprehensive Multi-Modal Framework for Population-Scale Liver Volumetry: Insights and Predictive Models

Authors: Mustafa Bashir, Diana Kadi, Kyle J. Lafata, Jacob A. Macdonald, Mark Martin, Yuqi Wang, Marilyn Yamamoto

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Department of Electrical and Computer Engineering, Duke University, Department of Radiology, Duke Unversity

Abstract Preview: Purpose: To develop a high-throughput, automated-data-interrogation pipeline for integrating imaging and clinical information to identify key determinants of liver volume (LV), enabling population-sca...

Enhanced Prognostic Modeling for Clear Cell Renal Cell Carcinoma Via Multi-Omics Model and Computational Pathology Foundation Model Integration

Authors: James Brugarolas, Meixu Chen, Raquibul Hannan, Payal Kapur, Jing Wang, Kai Wang

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

Abstract Preview: Purpose: Accurate prognosis of clear cell renal cell carcinoma (ccRCC) is essential for guiding personalized treatment planning. In this study, we present a multi-modal ensemble model (MMEM) that inte...

Exploring NSCLC Microenvironments: Multi-Score Survival Models Integrationg Radiomics-Based Regional Imaging Features and Genomics

Authors: Nobuki Imano, Daisuke Kawahara, Misato Kishi, Yuji Murakami

Affiliation: Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Graduate School of Biomedical and Health Sciences, Hiroshima University

Abstract Preview: Purpose: This study aims to develop a comprehensive Multi-score by integrating Radiomics-score (Rad-score), Gene-score derived from gene expression levels, and tumor environment Rad-score (TE-Rad-scor...

FMEA for Optimizing Patient-Specific QA Program in IMRT: Insights from Diverse Practices

Authors: Bing-Hao Chiang, Eric C. Ford, Juergen Meyer, Timothy D. Solberg

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

Abstract Preview: Purpose: This study evaluated the potential risk reduction of various pretreatment patient-specific quality assurance (PSQA) programs for Intensity Modulated Radiation Therapy (IMRT) in mitigating fai...

Film-Based Method for Accurate Radiation Isocenter Determination in Linear Accelerators Using 3D Starshot

Authors: Robert A. Corns, Mohammad Kanber

Affiliation: East Carolina University, East Carolina University Brody School of Medicine

Abstract Preview: Purpose:
Accurate determination of the radiation isocenter is crucial for precise radiotherapy treatments, directly impacting patient safety and treatment quality. This study presents a computation...

Improvements of Lateral Penumbra at Various Depth Regions in Scanned Proton Treatment System with a Multi-Leaf Collimator: Dose Verifications and Plan Comparisons

Authors: Takahiro Kato, Teiji Nishio, Masataka Oita, Robabeh Rahimi, Yuki Tominaga, Yushi Wakisaka

Affiliation: University of Maryland, Department of Radiological Sciences, School of Health Sciences, Fukushima Medical University, Medical Co. Hakuhokai, Osaka Proton Therapy Clinic, Medical Physics Laboratory, Division of Health Science, Osaka University Graduate School of Medicine, Faculty of Interdisciplinary Science and Engineering in Health Systems, Okayama University

Abstract Preview: Purpose: This study evaluated dose verifications and lateral penumbra improvements for scanned proton therapy plans with and without a multi-leaf collimator (MLC) under various air gaps.
Methods: E...

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...

Improving the Robustness of AI-Based Detection and Segmentation for Brain Metastasis By Optimizing Loss Function and Multi-Dataset Training

Authors: Omar Awad, Alfredo Enrique Echeverria, Issam M. El Naqa, Daniel Allan Hamstra, Yiding Han, Ryan Lafratta, Abdallah Sherif Radwan Mohamed, Piyush Pathak, Zaid Ali Siddiqui, Baozhou Sun, Vincent Ugarte

Affiliation: H. Lee Moffitt Cancer Center, Harris Health, Baylor College of Medicine

Abstract Preview: Purpose:
Accurate detection and segmentation of brain metastases are critical for diagnosis, treatment planning, and follow-up imaging but are challenging due to labor-intensive manual assessments ...

Interpretable Deep Learning Predicts Metastasis-Free Survival (MFS) from Conventional Imaging for Oligometastatic Castration-Sensitive Prostate Cancer (omCSPC) Using Multi-Modality PSMA PET and CT Imaging.

Authors: Yufeng Cao, Luigi Marchionni, William Silva Mendes, Cem Onal, Lei Ren, Amit Sawant, Nicole L Simone, Philip Sutera, Phuoc Tran

Affiliation: University of Maryland School of Medicine, 9Department of Radiation Oncology, Thomas Jefferson University, Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins Medicine, University of Maryland, Baltimore, Baskent University Faculty of Medicine, Department of Radiation Oncology, Department of Radiation Oncology, University of Maryland School of Medicine, Maryland University Baltimore, 8Department of Pathology and Laboratory Medicine, Weill Cornell Medicine

Abstract Preview: Purpose: This study aims to predict 2-yr Metastasis-free survival (MFS) for oligometastatic castration-sensitive prostate cancer (omCSPC) patients treated by metastasis-directed therapy (MDT) by devel...

LLM-Enhanced Multi-Modal Framework for Predicting Pain Relief of Stereotactic Body Radiotherapy for Spine Metastases Using Clinical Factors and Imaging Reports

Authors: John Byun, Steven D Chang, Mingli Chen, Cynthia Chuang, Xuejun Gu, Melanie Hayden Gephart, Yusuke Hori, Hao Jiang, Mahdieh Kazemimoghadam, Fred Lam, Gordon Li, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang, Qingying Wang, Zi Yang, Xianghua Ye, Kangning Zhang

Affiliation: Department of Radiation Oncology, Stanford University, Department of Neurosurgery, Stanford University, Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center, Department of Radiation Oncology, Stanford University School of Medicine

Abstract Preview: Purpose: Accurate prediction of pain relief is crucial in determining the clinical effectiveness of Stereotactic body radiotherapy (SBRT) regimen for spine metastases. We propose a deep-learning frame...

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...

Liver Tumor Auto-Contouring Using Recurrent Neural Networks on MRI-Linac for Adaptive Radiation Therapy

Authors: Yan Dai, Jie Deng, Christopher Kabat, Weiguo Lu, Ying Zhang, Hengrui Zhao

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

Abstract Preview: Purpose:
MRI-guided adaptive radiotherapy (MRgART) using MR-LINAC systems offers significant advantages for liver cancer, enabling superior tumor delineation and online plan adaptation. However, ma...

Lung-Equivalent Compressible Material As Core Component for a Miniaturized Breathing Phantom Prototype

Authors: Silvia Calusi, Lucia Cavigli, Alberto Dalla Mora, Laura Di Sieno, Giacomo Insero, Riccardo Lisci, Livia Marrazzo, Cosimo Nardi, Stefania Pallotta, Andrea Profili, Fulvio Ratto, Giovanni Romano, Michaela Servi, Immacolata Vanore, Yary Volpe

Affiliation: Italian National Research Council IFAC-CNR, Institute of Applied Physics, Department of Physics, Politecnico di Milano, Department of Agricultural Food and Forestry System, University of Florence, Medical Physics Unit, Azienda Ospedaliero-Universitaria Careggi, Department of Industrial Engineering, University of Florence, Department of Experimental and Clinical Biomedical Sciences “Mario Serio”, University of Florence

Abstract Preview: Purpose: To develop a multi-purpose lung phantom prototype to replicate respiratory dynamics and morphological features observed in clinical radiological (CT and MR) imaging of lung parenchyma.
Met...

Mapping Dosimetry, Excision Probability, and Mpmri Pixel Data to Core-Needle Biopsy Tissue from HDR Prostate Brachytherapy

Authors: Jeffrey Andrews, Nathan E. Becker, Juanita Crook, Andrew Jirasek, Matthew Jonathan Muscat

Affiliation: UBC, BC Cancer Agency, BC Cancer

Abstract Preview: Purpose: To map dosimetry and imaging information to ultrasound and multi-parametric magnetic resonance (mpMR) guided trans-perineal core-needle biopsies, performed during two-fraction prostate high-d...

Mitigating Discrepancies in Radiology Reports: A Robust LLM Approach for Generating Consistent Impressions

Authors: Junwen Liu, Mengzhen Wang, Ning Wen, Jifeng Xiao, Fuhua Yan, Yanzhao Yang, Xuekun Zhang, Zheyu Zhang

Affiliation: Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Department of Radiology, Ruijin Hospital Shanghai Jiaotong University School of Medicine, Shanghai Jiaotong University, The SJTU-Ruijin-UIH Institute for Medical Imaging Technology, Shanghai Jiaotong University Schoo of Medicine

Abstract Preview: Purpose:This study aims to develop and evaluate a large language model (LLM) fine-tuned to generate consistent and accurate impressions from imaging findings. Additionally, the study investigates the ...

Multi-Criteria Optimization in Medical Physics Resource Allocation: Design of an Efficient and Equitable Scheduling System

Authors: Dalton Griner, Kathryn L. Kolsky, Joseph John Lucido, Andrew J. Veres

Affiliation: Mayo Clinic

Abstract Preview: Purpose: This project aimed to automate a complex and time-consuming employee scheduling process. By replacing the traditional manual method with a multi-criteria optimization-based system (MCO), the ...

Multi-Modality Artificial Intelligence for Involved-Site Radiation Therapy: Clinical Target Volume Delineation in High-Risk Pediatric Hodgkin Lymphoma

Authors: Tyler J Bradshaw, Sharon M Castellino, Steve Y Cho, David Hodgson, Bradford S Hoppe, Kara M Kelly, Andrea Lo, Sarah Milgrom, Xin Tie

Affiliation: Department of Radiation Oncology, University of Toronto, Department of Radiology, University of Wisconsin, University of Colorado Anschutz, Department of Medical Physics, University of Wisconsin, Department of Radiation Oncology, Mayo Clinic, Department of Radiation Oncology, BC Cancer, Vancouver Center, Department of Radiology, University of Wisconsin - Madison, Roswell Park Comprehensive Cancer Center, Emory University School of Medicine

Abstract Preview: Purpose: Clinical target volume (CTV) delineation for involved-site radiation therapy (ISRT) in Hodgkin lymphoma (HL) is time-consuming due to the need to analyze multi-time-point PET/CT scans co-regi...

Multi-Organ Segmentation of Pelvic Cone-Beam Computed Tomography (CBCT) with Transformer Models to Enhance Adaptive Radiotherapy for Prostate Cancer

Authors: Ming Chao, Thomas Chum, Tenzin Kunkyab, Yang Lei, Tian Liu, Richard G Stock, Hasan Wazir, Junyi Xia, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose:
This study aims to develop effective strategies for multi-organ segmentation of pelvic cone-beam computed tomography (CBCT) images based on transformer models to facilitate adaptive radiat...

Multimodal Attention Fusion Model Leveraging Structured and Unstructured EHR Data for Hospital Readmission Prediction in Head and Neck Cancer

Authors: Shreyas Anil, Jason Chan, Arushi Gulati, Yannet Interian, Hui Lin, Benedict Neo, Andrea Park, Bhumika Srinivas

Affiliation: Department of Otolaryngology Head and Neck Surgery, University of California San Francisco, Department of Data Science, University of San Francisco, Department of Radiation Oncology, University of California San Francisco

Abstract Preview: Purpose: Hospital readmission prediction models often rely on structured Electronic Health Record (EHR) data, overlooking critical insights from unstructured clinical notes. This study presents a mult...

Novel Approach to Improve Treatment Planning Process for Mixed Fractionation Schemes on ZAP-X

Authors: Michael Evan Chaga, Timothy Chen, Darra M. Conti, Shabbar Danish, Jing Feng, Wenzheng Feng, Joseph Hanley, Tingyu Wang

Affiliation: Hackensack Meridian Health, Jersey Shore University Medical Center

Abstract Preview: Purpose: Using mixed fractionation schemes is a common technique in treating CNS lesions. This article describes an innovative plan-and-split approach for more efficient planning on the ZAP-X and thus...

Patient-Specific Imaging Modality Agnostic Virtual Digital Twins Modeling Temporally Varying Digestive Motion

Authors: James M. Balter, Lando S. Bosma, Jorge Tapias Gomez, Nishant Nadkarni, Mert R Sanbuncu, William Paul Segars, Ergys D. Subashi, Neelam Tyagi, Harini Veeraraghavan

Affiliation: University of Michigan, The University of Texas MD Anderson Cancer Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Cornell University, University Medical Center Utrecht, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: Develop patient-specific virtual digital twin (VDT) cohorts modeling physically realistic spatio-temporal gastrointestinal (GI) organs (stomach and duodenum) digestive motion.
Methods: Pat...

Precision Radiotherapy Dose Prediction Using Foundation Model-Augmented Learning

Authors: Hilary P Bagshaw, Mark K Buyyounouski, Xianjin Dai, PhD, Praveenbalaji Rajendran, Lei Xing, Yong Yang

Affiliation: Department of Radiation Oncology, Stanford University, Massachusetts General Hospital, Harvard Medical School

Abstract Preview: Purpose: Artificial intelligence (AI)-driven methods have transformed dose prediction, streamlining the automation of radiotherapy treatment planning. However, traditional approaches depend exclusivel...

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...

Remote Evaluation of Flash Beamlines for Electron, Proton, and MV Photons

Authors: Alexander Baikalov, Luke Connell, Nolan M. Esplen, Michele M. Kim, Stephen F. Kry, Emil Schueler, Hayden Scott, Ryan Sun, Paige A. Taylor, Uwe Titt

Affiliation: The University of Texas MD Anderson Cancer Center, University of Pennsylvania, UT MD Anderson Cancer Center, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center

Abstract Preview: Purpose: to develop an affordable, portable device for accurately measuring FLASH dose rates from protons, electrons, and photons. 4 detectors were utilized to measure the temporal structure of proton...

SPECT/CT Multimodal Segmentation of Bone Marrow for Theranostic Dosimetry

Authors: Tommaso Frigerio, Joshua Genender, John M. Hoffman, Catherine (Caffi) Meyer

Affiliation: UCLA, David Geffen School of Medicine at UCLA

Abstract Preview: Purpose: Accurate bone marrow segmentation is required for bone marrow dosimetry to monitor for dangers in PSMA-Lu177 radioligand therapy. We introduce a hybrid (AI/semantic knowledge) segmentation pi...

Small but Mighty: A Lightweight and Computationally Efficient Model for Deformable Image Registration

Authors: Hengjie Liu, Dan Ruan, Ke Sheng, DI Xu

Affiliation: Physics and Biology in Medicine, University of California, Los Angeles, Department of Radiation Oncology, University of California, San Francisco, Department of Radiation Oncology, University of California at San Francisco, Department of Radiation Oncology, University of California, Los Angeles

Abstract Preview: Purpose:
State-of-the-art deep learning-based deformable image registration often uses large, complex models directly adapted from computer vision tasks but achieves only comparable performance to ...