Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Gregory Szalkowski, Qingying Wang, Kangning Zhang
Affiliation: 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: Respiratory motion management is crucial for accurate radiation delivery to moving targets while protecting healthy tissue, relying on time-resolved volumetric imaging and continuous deformab...
Authors: Jie Deng, Yunxiang Li, Xiao Liang, Weiguo Lu, Jiacheng Xie, You Zhang
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, University of Texas Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center, The University of Texas at Dallas
Abstract Preview: Purpose: Recently, foundational models trained on large datasets have shown remarkable performance across various tasks. Developing a foundational model for medical image modality translation in head-...
Authors: Beth M. Beadle, Adrian Celaya, Laurence Edward Court, David Fuentes, Anna Lee, Tze Yee Lim, Dragan Mirkovic, Amy Moreno, Raymond Mumme, Tucker J. Netherton, Callistus M. Nguyen, Jaganathan A Parameshwaran, Jack Phan, Carlos Sjogreen, Sara L. Thrower, Congjun Wang, He C. Wang, Xin Wang
Affiliation: Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Department of Radiation Oncology, Stanford University, The University of Texas MD Anderson Cancer Center, MD Anderson Cancer Center, MD Anderson, Rice University, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose: Quality assurance of target volumes from radiotherapy clinical trials is a labor and resource intensive task. The purpose of this work is to quantify the accuracy of a tool that automatically...
Authors: Eric Chang, Nguyen Phuong Dang, Andrew Lim, Lauren Lukas, Lijun Ma, Yutaka Natsuaki, Zhengzheng Xu, Hualin Zhang
Affiliation: Radiation Oncology, Keck School of Medicine of USC
Abstract Preview: Purpose: Harnessed the power of AI and Deep Learning (DL), Generalized Neural Network models for medical image transformation are trained to predict target images from reference images, often requirin...
Authors: Charmainne Cruje, Maria Dumol, Nawroz Fatima, Marisa Finlay, Kalaina Johnson, Raman Mohla, Jasleen Uppal
Affiliation: Trillium Health Partners, Carlo Fidani Regional Cancer Centre
Abstract Preview: Purpose: To evaluate the robustness of a breast SBRT protocol in achieving target coverage by utilizing online- and retrospectively-matched CBCT-to-CT images.
Methods: The first pilot patient was s...
Authors: Zijia Guo, Michael F. McNitt-Gray, Frederic Noo, Karl Stierstorfer
Affiliation: Siemens Healthineers, University of Utah, David Geffen School of Medicine at UCLA
Abstract Preview: Purpose: Accurately assessing lung parenchyma health is critically important in the management of patients with chronic obstructive pulmonary disease. CT attenuation values are valuable for this purpo...
Authors: Rani Anne', Wenchao Cao, Yingxuan Chen, Wookjin Choi, Firas Mourtada, Yevgeniy Vinogradskiy
Affiliation: Thomas Jefferson University
Abstract Preview: Purpose: In-room mobile cone-beam CT (CBCT) is emerging to enhance high-dose-rate (HDR) brachytherapy workflow using on-demand imaging. However, metal artifacts from X-ray markers inside gynecological...
Authors: Penghao Gao, Zejun Jiang
Affiliation: Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Artificial Intelligence Laboratory, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences
Abstract Preview: Purpose: Real-time tumor tracking can effectively compensate for the impact of respiratory motion on dose distribution. We propose a patient-specific external-internal correlation model driven by opti...
Authors: Pradeep Bhetwal, Wookjin Choi, Adam Dicker, Rupesh Ghimire, Yingcui Jia, Lauren Nkwonta, Yevgeniy Vinogradskiy, Wentao Wang, Maria Werner-Wasik
Affiliation: Thomas Jefferson University
Abstract Preview: Purpose: Multi-disciplinary clinics are becoming standard of care for patients with lung cancer treated with SBRT. To improve clinical decision support in a multi-disciplinary clinic, it would be bene...
Authors: Zilei Fu, Yi Guo, Wanli Huo, Hongdong Liu, Laishui Lyu, Zhao Peng, Yaping Qi, Senting Wang
Affiliation: Department of Radiotherapy, cancer center, The First Affiliated Hospital of Fujian Medical University, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Division of lonizing Radiation Metrology, National Institute of Metrology, 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, Department of Oncology, Xiangya Hospital, Central South University
Abstract Preview: Purpose: Medical image boundaries are commonly characterized by smooth gray-level transitions, resulting in pixel-level segmentation errors near these blurred boundaries. To address this, we developed...
Authors: Shae Gans, Carri K. Glide-Hurst, Mark Pankuch, Chase Ruff, Niek Schreuder, Nicholas R. Summerfield, Yuhao Yan
Affiliation: Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Northwestern Medicine Proton Center, Northwestern Medicine Chicago Proton Center, Leo Cancer Care
Abstract Preview: Purpose: Novel upright patient positioners coupled with diagnostic-quality vertical CT at treatment isocenter introduce a significant opportunity for improved image-guided particle therapy. Treating p...
Authors: Lavsen Dahal, Francesco Ria, Ehsan Samei, Justin B. Solomon, Liesbeth Vancoillie, Yakun Zhang
Affiliation: Duke University, Carilion Clinic, Clinical Imaging Physics Group, Department of Radiology, Duke University Health System
Abstract Preview: Purpose: Clinical diagnostic task-based optimization of CT procedures require precise and organ-specific assessments. This study investigates inter-organ noise variability to highlight the limitations...
Authors: John T Barrett, Mehnaz Haque, Chulhaeng Huh, Shands James, Thomas B. Lavin, Anobel Maghsoodpour, Farshad Mostafaei, Austin Sanders
Affiliation: Department of Radiation Oncology, Augusta University, Department of Radiation Oncology, Medical College of Georgia, Augusta University, Georgia Radiation Therapy Center, Wellstar-MCG Health, Department of Radiation Oncology, Doctors Hospital of Augusta, Department of Radiology and Imaging, Augusta University
Abstract Preview: Purpose: This study assesses Philipsâ O-MAR effectiveness in adjusting AVHU values of common anatomical materials affected by various high-density metal artifacts at varying distances.
Methods:...
Authors: Chuangxin Chu, Haotian Huang, Tianhao Li, Jingyu Lu, Zhenyu Yang, Fang-Fang Yin, Tianyu Zeng, Chulong Zhang, Yujia Zheng
Affiliation: The Hong Kong Polytechnic University, Nanyang Technological University, Australian National University, Medical Physics Graduate Program, Duke Kunshan University, North China University of Technology, Duke Kunshan University
Abstract Preview: Purpose: Deep learning segmentation models, such as U-Net, rely on high-quality image-segmentation pairs for accurate predictions. However, the recent increasing use of generative networks for creatin...
Authors: Ashish Binjola, Raj Kishore Bisht, Natanasabapathi Gopishankar, Pratik Kumar, Daya Nand Kishore Sharma, Sukhvir Kishore Singh, Subramani Vellaiyan
Affiliation: Medical Physics Unit, All India Institute of Medical Sciences, All India Institute of Medical Sciences, Department of Radiological Safety, Institute of Nuclear Medicine and Allied Sciences, Department of Radiation Oncology, All India Institute of Medical Sciences
Abstract Preview: Purpose: Additive manufacturing is increasingly being explored to create dosimetry phantoms. Commercial anthropomorphic phantoms represent an average patient and lack anatomical variations due to obes...
Authors: Austin Castelo, Xinru Chen, Caroline Chung, Laurence Edward Court, Jaganathan A Parameshwaran, Zhan Xu, Jinzhong Yang, Yao Zhao
Affiliation: The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center
Abstract Preview: Purpose:
To develop a deep learning-based segmentation model to automatically delineate tumors from full-body PET/CT images.
Methods:
PET/CT image pairs of 91 patients were collected for this...
Authors: Quan Chen, Xue Feng, Chunhui Han, Gaofeng Huang, Trevor Ketcherside, Yi Lao, Yun Rose Li, An Liu, Bo Liu, Kun Qing, William T. Watkins
Affiliation: Graduate Program in Bioengineering, University of California San Francisco-UC Berkeley, Department of Radiation Oncology, City of Hope National Medical Center, Mayo Clinic Arizona, Carina Medical LLC
Abstract Preview: Purpose: New treatment platforms such as Ethos (Varian Medical Systems) allow the introduction of multi-modal imaging into adaptive radiotherapy workflow to facilitate an up-to-date view of patientsâ ...
Authors: Hailun Pan, Yingli Yang, Jie Zhang, Yibin Zhang
Affiliation: Department of Radiation Oncology,Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Department of Radiology, Ruijin Hospital, Department of Radiation Oncology, Ruijin Hospital, , Shanghai Jiaotong University School Of Medicine, Shanghai United imaging Healthcare Advanced Technology Research Institute
Abstract Preview: Purpose: Accurate patient positioning is critical in radiotherapy (RT) to ensure effective treatment delivery and minimize harming surrounding healthy tissues. Vertebral misalignment during RT setup h...
Authors: Hongyi Jiang, Fang-Fang Yin
Affiliation: Duke University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose:
Imaging moving tissues using PET-CT can be difficult. Separating signal into phases during construction reduces signal count and increases influence of noise. Algorithms that use signal fr...
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...
Authors: Liyuan Chen, Steve Jiang, Chenyang Shen
Affiliation: Department of Radiation Oncology, UT Southwestern Medical Center, UT Southwestern Medical Center
Abstract Preview: Purpose: Delays in radiation therapy (RT) initiation caused by conventional CT simulation processes can hinder timely treatment delivery and patient outcomes. This study proposes a Virtual Treatment S...
Authors: Kristen A. Duke, Samer Jabor, Neil A. Kirby, Parker New, Niko Papanikolaou, Arkajyoti Roy, Yuqing Xia
Affiliation: St. Mary's University, The University of Texas San Antonio, UT Health San Antonio
Abstract Preview: Purpose:
The Segment Anything Model (SAM) is a foundational box-prompt-based model for natural image segmentation. However, its applicability to zero-shot 3D medical image segmentation, particularl...
Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Kangning Zhang
Affiliation: 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:
PET is used in radiotherapy workflows for accurate target delineation. However, a separate CT scan is typically required for attenuation correction in PET imaging and for registering PET-d...
Authors: Austen N. Curcuru, Arash Darafsheh, Winter Green, Yao Hao, Baozhou Sun, Tiezhi Zhang, Tianyu Zhao, Xiandong Zhao
Affiliation: WashU Medicine, Washington University School of Medicine, Department of Radiation Oncology, Washington University School of Medicine, Washington University in St. Louis, University of South Florida, Baylor College of Medicine
Abstract Preview: Purpose: Intensity modulated proton therapy (IMPT) requires precise setup imaging due to the sharp dose gradients and rapid distal fall-off seen in proton therapy dose distributions. Additionally, onl...
Authors: Ergun E. Ahunbay, Colette Gage, Abdul Kareem Parchur, Eric S. Paulson
Affiliation: Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose: AI-generated synthetic CT (sCT) images address challenges with prior sCT approaches, including atlas- and threshold-based methods. Commercial AI-based sCT tools have been introduced. This wor...
Authors: Carla D. Bradford, Linda Ding, Yansong Geng, Alan Hartford, I-Lin Kuo, Salvatore LaRosa, Joshua N Wancura
Affiliation: University of Massachusetts Chan Medical School
Abstract Preview: Purpose: When treating nasal skin cancers, electron beam radiotherapy dose distributions can be improved by using custom bolus to compensate for uneven surfaces. Here we describe our experience commis...
Authors: Theodore Higgins Arsenault, Beatriz Guevara, Rojano Kashani, Raymond F. Muzic, Gisele Castro Pereira, Alex T. Price
Affiliation: University Hospitals Seidman Cancer Center, Case Western Reserve University Department of Biomedical Engineering
Abstract Preview: Purpose: Accurate dose prediction in radiotherapy is essential for treatment planning. This study evaluates four nnUnet-based models using the OpenKBP head and neck dataset: a baseline model (Model 1)...
Authors: Aditya P. Apte, Joseph O. Deasy, Jue Jiang, Nancy Lee, Sudharsan Madhavan, Nishant Nadkarni, Lopamudra Nayak, Harini Veeraraghavan, Wei Zhao
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: To track early response to radiotherapy using digital twins, it is crucial to quantify tumor volume and mass changes. Traditional tumor detection methods, particularly in image registration, ...
Authors: Ryan Andosca, Igor Barjaktarevic, Peter Boyle, Jie Deng, Minji Victoria Kim, Michael Vincent Lauria, Daniel A. Low, Claudia R. Miller, Drew Moghanaki, Louise Naumann, Jack Neylon, Dylan P. O'Connell, Ricky R Savjani
Affiliation: Department of Pulmonology, University of California Los Angeles, University of California, Los Angeles, Department of Radiation Oncology, University of California, Los Angeles, UCLA, UCLA Radiation Oncology
Abstract Preview: Purpose: To develop a Hounsfield Unit ventilation-based correction method for use with model-based CT when used as a replacement for 4DCT.
Methods: The model-based CT we employ is termed 5DCT, whic...
Authors: Xu Chen, Jun Lian, Yunkui Pang, Pew-Thian Yap
Affiliation: University of North Carolina at Chapel Hill, Huaqiao University
Abstract Preview: Purpose: Unsupervised CBCT-to-CT translation in the pelvic region is essential for accurate radiotherapy delivery and adaptive image-guided interventions. However, current models for cross-modality tr...
Authors: Hector Andrade-Loarca, Ines Butz, Chiara Gianoli, Prof. Gitta Kutyniok, Jianfei Li, Katia Parodi, Prof. Vincenzo Patera, Angelo Schiavi, Prof. Ozan Ăktem
Affiliation: Sapienza University of Rome, Department of Mathematics, Royal Institute of Technology, School of Computation, Information and Technology, Technische Universitaet Muenchen, Department of Medical Physics, Ludwig-Maximilians-Universität Mßnchen (LMU Munich), Department of Mathematics, Ludwig-Maximilians-Universität (LMU) Mßnchen, Department of Medical Physics, Ludwig-Maximilians-Universität (LMU) Mßnchen
Abstract Preview: Purpose: To explore and demonstrate the feasibility of accurate and fast prediction of the water equivalent thickness (WET) distribution of tissue traversed by a proton imaging pencil beam, aiming at ...
Authors: Zhuo Chen, Tinsu Pan, Allan Thomas
Affiliation: Mallinckrodt Institute of Radiology, Washington University School of Medicine, WashU Medicine, UT MD Anderson Cancer Center
Abstract Preview: Purpose: Misregistration between data-driven gated (DDG)-PET and CT can limit the benefits of motion correction and improved localization and quantitation. DDG-CT offers a solution to these issues. He...
Authors: Mark Bowers, Gabriel Carrizo, Jimmy Caudell, Vladimir Feygelman, Kevin Greco, Christian Hahn, Jihye Koo, Kujtim Latifi, Fredrik Lofman, Jacopo Parvizi, Muqeem Qayyum, Caleb Sawyer
Affiliation: RaySearch Laboratories, Moffitt Cancer Center
Abstract Preview: Purpose: Head and neck (H&N) radiotherapy planning is complex, with multiple competing objectives. We endeavored to improve efficiency of planning by developing a deep learning (DL) model trained to p...
Authors: Laila A Gharzai, Bharat B Mittal, Poonam Yadav
Affiliation: Northwestern Feinberg School of Medicine, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Northwestern University Feinberg School of Medicine
Abstract Preview: Purpose: Multiple studies have shown the increasing role of deep learning in segmenting regions of interest. This work presents the feasibility of auto-segmenting the critical structures for head and ...
Authors: Yaspal Badyal, Rabten Datsang, Tianjun Ma, William Song
Affiliation: MVision AI, Virginia Commonwealth University
Abstract Preview: Purpose: Deep learning (DL)-based dose distribution predictions for prostate cancer show significant potential for OAR sparing compared to manually optimized treatment plans. We aim to generate clinic...
Authors: Fumiaki Komatsu, Shunsuke Moriya, Ryosuke Nakamura, Takeji Sakae, Toshiyuki Terunuma, Tetsuya Tomita
Affiliation: Graduate School of Comprehensive Human Sciences, University of Tsukuba, Institute of Medicine, University of Tsukuba, Proton Medical Research Center, University of Tsukuba, Department of Radiology, University of Tsukuba Hospital
Abstract Preview: Purpose: To develop a deep learning (DL) model capable of accurately tracking lung tumors independent of beam angle variations.
Methods: A thoracic dynamic phantom simulating lung motion in the sup...
Authors: John Byun, Juan J Cardona, Steven D Chang, Cynthia Fu-Yu Chuang, Xuejun Gu, Yusuke Hori, Hao Jiang, Fred Lam, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang
Affiliation: Department of Radiation Oncology, Stanford University, Department of Neurosurgery, Stanford School of Medicine, 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:
Intraventricular tumors pose significant challenges in neurosurgery due to their complex location. Therefore, brain SRS could be a better treatment option. At our institution, some patient...
Authors: Matthew Stephen Andriotty, Taoran Cui, Harold Y Hu, Ke Nie, Tan Phan, Xiao Wang, Ning J. Yue, Chengzhu Zhang
Affiliation: Rutgers Cancer Institute of New Jersey, Basis Scottsdale
Abstract Preview: Purpose: Metallic implants are often non-isocentric, and their exact volumes/orientations/shapes are difficult to capture and contour accurately on CT images even if that information is known beforeha...
Authors: Mohamed Bahaaeldin Mohamed Afifi, Nahla Nagy Ahmad Ataalla, Ahmed A. Eldib
Affiliation: Fox Chase Cancer Center, Radiological Sciences and Medical Imaging Department, College of Applied Medical Sciences, Prince Sattam bin Abdulaziz University.
Abstract Preview: Purpose: Optimizing CT imaging parameters is crucial for balancing radiation dose, contrast resolution, and accurate Hounsfield unit representation, particularly in radiotherapy treatment planning. Th...
Authors: John Byun, Steven D Chang, Cynthia Fu-Yu Chuang, Xuejun Gu, Melanie Hayden Gephart, Yusuke Hori, Fred Lam, Gordon Li, Lianli Liu, Weiguo Lu, David Park, Erqi Pollom, Elham Rahimy, Deyaaldeen Abu Reesh, Scott Soltys, Gregory Szalkowski, Lei Wang, Xianghua Ye, Kangning Zhang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Department of Neurosurgery, Stanford University, Department of Radiation Oncology, Stanford University, Department of Radiation Oncology, Stanford University School of Medicine
Abstract Preview: Purpose: Accurate and automated delineation of vestibular schwannoma (VS) volume is crucial for disease management, as both treatment approaches (stereotactic radiosurgery and invasive surgery) and mo...
Authors: Victoria Doss, Tsion Gebre, Rachel B. Ger, Esi A Hagan, Elaina Hales, Russell K Hales, Xun Jia, Heng Li, Dezhi Liu, Todd R. McNutt, Meti Negassa, Anas Obaideen, Tinker Trent, K. Ranh Voong, Cecilia FPM de Sousa
Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Johns Hopkins University
Abstract Preview: Purpose: As cancer care advances, more patients require re-irradiation, yet evidence-based data is lacking. This study aimed to develop a thoracic re-irradiation database and explore time-dependent re...
Authors: Chang Chang, Mohammad Kanber, Stephen Kenneth Northway
Affiliation: East Carolina University, California Protons Cancer Therapy Center, California Proton Cancer Therapy Center
Abstract Preview: Purpose:
Proton therapy treatment planning involves the consideration of unique physical quantities such as Linear Energy Transfer (LET) and spot location maps that do not exist in photon treatment...
Authors: Theodore Higgins Arsenault, Kenneth W. Gregg, Lauren E Henke, Rojano Kashani, Haley K Perlow, Alex T. Price, Atefeh Rezaei, Prashant Vempati, Runyon C. Woods
Affiliation: University Hospitals Seidman Cancer Center
Abstract Preview: Purpose: The HyperSight imaging feature on C-arm linacs(HS-CBCT) offers increased CT number accuracy over conventional on-board imaging. The C-arm geometry allows for noncoplanar treatments common to ...
Authors: Xiaoyi Dai, Manju Liu, Weiwei Sang, Pulin Sun, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Rihui Zhang
Affiliation: Jiahui International Hospital, Radiation Oncology, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University
Abstract Preview: Purpose:
Current deep learning-based sparse-view CBCT reconstruction methods are prone to hallucinatory artifacts, as they rely on inferred image details that may not correspond to true anatomical ...
Authors: Daniel H. Bushe, Arthur Lalonde, Hoyeon Lee, Harald Paganetti, Brian Winey
Affiliation: Universite de Montreal, Massachusetts General Hospital, Massachusetts General Hospital and Harvard Medical School, University of Hong Kong
Abstract Preview: Purpose: Improving the precision and fidelity of daily volumetric imaging is essential for enabling adaptive proton therapy (APT). While cone-beam CT (CBCT) provides daily volumetric imaging, their ut...
Authors: Rashmi Bhaskara, Oluwaseyi Oderinde
Affiliation: Purdue University
Abstract Preview: Purpose: This study proposes a novel approach to overcoming CBCT image quality limitations by developing an improved synthetic CT (sCT) generation method based on a CycleGAN architecture using Vision ...
Authors: Yi-Fang Wang, Yading Yuan
Affiliation: Columbia University Irving Medical Center, Department of Radiation Oncology, Columbia University Irving Medical Center
Abstract Preview: Purpose: HyperSight, the latest CBCT technology from Varian Medical Systems, integrates rapid 6-second data acquisition with advanced iterative reconstruction and upgraded hardware. Previous studies h...
Authors: Theodore Higgins Arsenault, Kenneth W. Gregg, Lauren E Henke, Rojano Kashani, Alex T. Price, Sagar Regmi, Atefeh Rezaei, Runyon C. Woods
Affiliation: University Hospitals Seidman Cancer Center
Abstract Preview: Purpose: To investigate the feasibility and accuracy of using a Hounsfield Unit(HU) calibrated cone-beam computed tomography(CBCT) for direct dose calculation in thoracic treatment settings. In combin...
Authors: Haleem Azmy, Robbie Beckert, Farnoush Forghani, Dean Hobbis, Dan Hong, Hyun Kim, Eric Laugeman, Silpa Raju-Salicki, Domenic Sievert
Affiliation: Washington University in St. Louis School of Medicine, WashU Medicine, Washington University School of Medicine, Department of Radiation Oncology, Washington University School of Medicine in St. Louis, Washington University School of Medicine, Wash U Medicine, Washington University in St. Louis
Abstract Preview: Purpose: A novel radiation therapy (RT) workflow has recently emerged with the advent of online adaptive RT systems, direct-to-unit (DTU). DTU utilizes online adaptive platforms (MR and CT based) to o...
Authors: Claus Belka, Stefanie Corradini, George Dedes, Nikolaos Delopoulos, Christopher Kurz, Guillaume Landry, Ahmad Neishabouri, Domagoj Radonic, Adrian Thummerer, Niklas Wahl, Fan Xiao
Affiliation: Department of Radiation Oncology, LMU University Hospital, LMU Munich, Department of Medical Physics, LMU Munich, Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), National Center for Radiation Oncology (NCRO), Heidelberg Institute for Radiation Oncology (HIRO)
Abstract Preview: Purpose: In MR-guided online adaptive radiotherapy, MRI lacks tissue attenuation information necessary for accurate dose calculations. Instead of using deep learning methods to generate synthetic CT i...
Authors: Xinyuan Chen, Geoffrey D. Hugo, Alex T. Price, Pamela Samson, Tianyu Zhao
Affiliation: University Hospitals Seidman Cancer Center, University of South Florida, Washington University School of Medicine, WashU Medicine
Abstract Preview: Purpose: This study evaluates the financial viability of on-table simulation (CBCTp) enabled Halcyon system in radiation therapy. By leveraging Time-Driven Activity-Based Costing (TDABC), the analysis...
Authors: Xinyuan Chen
Affiliation: Washington University School of Medicine
Abstract Preview: Purpose: This study evaluates the financial viability of on-table simulation (CBCTp) enabled Halcyon system in radiation therapy. By leveraging Time-Driven Activity-Based Costing (TDABC), the analysis...
Authors: Mingli Chen, Xuejun Gu, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Department of Radiation Oncology, Stanford University School of Medicine
Abstract Preview: Purpose: This study introduces a novel template-guided deep learning framework for primary gross tumor volume (GTVp) segmentation, addressing challenges posed by diverse tumor types and enabling a uni...
Authors: Xianjin Dai, PhD, Michael Gensheimer, Praveenbalaji Rajendran, Lei Xing, Yong Yang
Affiliation: Department of Radiation Oncology, Stanford University, Massachusetts General Hospital, Harvard Medical School
Abstract Preview: Purpose: Recent advances in the automatic delineation of radiotherapy treatment targets, which incorporate linguistic clinical data extracted by large language models (LLMs) into traditional visual-on...
Authors: Md. Yousuf Ali, Parvin Akhter Banu, Ehteshamul Hoque, Qazi Mushtaq Hussain, Md Jobairul Islam, Md. Abdul Mannan, Sadia Afrin Sarah, Mostafa Aziz Sumon, Ahammad Al Mamun Sweet, AFM Kamal Uddin
Affiliation: Labaid Cancer Hospital & Superspeciality Centre
Abstract Preview: Purpose: Radiotherapy for left-sided breast cancer can induce cardiac injury. Deep Inspiration Breath Hold (DIBH) is a technique that minimizes cardiac exposure during treatment. This study compares d...
Authors: Girish Bal, Jan Kralj, Ayan Mitra, PhD, Ling Shao, Matjaz Subic, Yevgen Voronenko
Affiliation: RefleXion Medical, Cosylab
Abstract Preview: Purpose: This work enhances the efficiency of radiation therapy treatment planning by optimizing the beamlet dose matrix and full patient dose computations using GPU acceleration. The Collapsed-Cone C...
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...
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...
Authors: Rodrigo T Massera, Sofia Giaccone Thomaz, Alessandra Tomal, Giovanna Tramontin
Affiliation: Universidade Estadual de Campinas. Instituto de FĂsica Gleb Wataghin, Department of Imaging & Pathology, unit of Medical Physics & Quality Assessment, KU Leuven
Abstract Preview: Purpose: Monte Carlo simulations are increasingly used in breast dosimetry for their precision in estimating difficult-to-measure quantities, such as glandular dose. With ionizing radiation in breast ...
Authors: So Hyun Ahn, Chris Beltran, Byongsu Choi, Jeong Heon Kim, Jin Sung Kim, Bo Lu, Justin Chunjoo Park, Bongyong Song, Jun Tan
Affiliation: Mayo Clinic, Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine, Ewha Medical Research Institute, Ewha Womans University College of Medicine, UC San Diego, Yonsei University College of Medicine
Abstract Preview: Purpose:
Cone-beam computed tomography (CBCT) is widely used in IGRT for patient positioning but suffers from low resolution and poor soft tissue contrast. Synthetic CT (sCT) generated from CBCT ad...
Authors: Max Chen, Sean Marquardt, Ben Yang, Kai Yang
Affiliation: Cary Academy, Massachusetts General Hospital, Winchester High School
Abstract Preview: Purpose: To analyze the impact of scanner model variation on the effective dose conversion factor (âk-factorâ), which is most commonly used for CT effective dose calculation.
Methods: The stand...
Authors: Theodore Higgins Arsenault, Kenneth W. Gregg, Lauren E Henke, Rojano Kashani, Christian Erik Petersen, Alex T. Price, Atefeh Rezaei, Runyon C. Woods
Affiliation: University Hospitals Seidman Cancer Center
Abstract Preview: Purpose: CBCT is subject to more artifacts due to increased photon scatter, especially in areas of increased tissue heterogeneities compared to fan-beam CTs (FBCTs). Improved imaging panels combined w...
Authors: Steve B. Jiang, Chien-Yi Liao, Dan Nguyen, Daniel Yang, Hengrui Zhao
Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose:
Post-operative radiotherapy for prostate cancer requires precise contouring of the clinical target volume (CTV) to account for microscopic disease that is invisible in the image. However, ...
Authors: Wendy Siman, Wei Zhou
Affiliation: University of Colorado Anschutz Medical Campus, School of Medicine
Abstract Preview: Purpose:
To compare the image quality and radiation dose of 3D cone-beam CT modes of a mobile C-arm and an O-arm unit for intraoperative imaging.
Methods:
A 50-Âľm tungsten wire was imaged at ...
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...
Authors: Ali Ajdari, Thomas R. Bortfeld, Christopher Bridge, Gregory Buti, Marcela Giovenco, Fredrik Lofman, Gregory C. Sharp, Helen A Shih, Tugba Yilmaz
Affiliation: Massachusetts General Hospital, RaySearch Laboratories, Department Of Radiation Oncology, Massachusetts General Hospital (MGH), Massachusetts General Hospital & Harvard Medical School, Massachusetts General Hospital and Harvard Medical School
Abstract Preview: Purpose: Defining radiation target volumes with accurate integration of the neuroanatomy is one of the major difficulties in designing glioma treatments. We developed a deep learning network for norma...
Authors: Mark Anastasio, Hua Li, Zhuchen Shao
Affiliation: Washington University School of Medicine, University of Illinois Urbana-Champaign
Abstract Preview: Purpose: Ill-conditioned reconstruction problems in medical imaging, such as those arising from undersampled k-space data in MRI, can result in degraded image quality and clinical task-orientated perf...
Authors: Harald Keller, Iymad Mansour, Jeff D. Winter
Affiliation: Princess Margaret Cancer Centre
Abstract Preview: Purpose: The growing number of adaptive therapy applications is motivating image segmentation and direct dose calculation on CBCT. The purpose of this investigation is to evaluate the recently release...
Authors: Matthew R. Hoerner, Allison Shields
Affiliation: Yale University School of Medicine, Yale University
Abstract Preview: Purpose: To investigate the quality and clinical utility of chest x-rays synthesized from CT scans (sCXR).
Methods: Five helical chest CT exams were chosen for evaluation: this cohort represented a...
Authors: Justus Adamson, John Ginn, Yongbok Kim, Ke Lu, Trey Mullikin, Xiwen Shu, Chunhao Wang, Zhenyu Yang, Jingtong Zhao
Affiliation: Duke University, Duke Kunshan University
Abstract Preview: Purpose:
To develop a knowledge-based deep model for synthetic CT (sCT) generation from a single MR volume in frameless radiosurgery (SRS), eliminating the need for CT simulation prior to the SRS d...
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 âMario Serioâ, 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...
Authors: Andrew R. Godley, Steve B. Jiang, Mu-Han Lin, Austen Matthew Maniscalco, Dan Nguyen, Yang Kyun Park
Affiliation: 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, Medical Artificial Intelligence and Automation (MAIA) Lab & Department of Radiation Oncology, UT Southwestern Medical Center
Abstract Preview: Purpose:
Preparing DICOM datasets for research and education is challenging due to the complexity of the format and the necessity for patient-specific handling. Existing workflows demand substantia...
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...
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...
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...
Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Kangning Zhang
Affiliation: 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:
Deep learning-based automatic medical image segmentation is increasingly employed in clinical practice, significantly reducing manual workload. However, verifying segmentation results rema...
Authors: Samuel L. Brady, Shruti Hegde, Alexander Knapp, Usman Mahmood, Joseph G. Meier, Elanchezhian Somasundaram, Zachary Taylor
Affiliation: Cincinnati Children's Hospital Medical Ctr, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Cincinnati Children's Hospital Medical Center, Cincinnati Childrens Hospital Med Ctr
Abstract Preview: Purpose:
To assess how two benchmark multi-organ CT segmentation models respond to varying image noise levels.
Methods:
This study utilized the pediatric CT dataset from The Cancer Imaging Ar...
Authors: Keyi Bian, Marco Caballo, Wenxiu Guo, Haijie Li, Jiao Li, Aidi Liu, Yue Ma, Ioannis Sechopoulos, Yafei Wang, Yaopan Wu, Zhaoxiang Ye, Yuwei Zhang, Yueqiang Zhu, Daan van den Oever
Affiliation: Radboud University Medical Center, Tianjin Medical University Cancer Institute & Hospital, Sun Yat-Sen University Cancer Center
Abstract Preview: Purpose: To develop and validate a nomogram integrating intra- and peritumoral radiomics of contrast-enhanced cone-beam breast CT (CE-CBBCT) and clinicopathologic features for predicting fluorescence ...
Authors: Ibtisam Almajnooni, Victor Cobilean, Milos Manic, Harindra Sandun Mavikumbure, Elisabeth Weiss, Lulin Yuan
Affiliation: Virginia Commonwealth University
Abstract Preview: Purpose: This study aims to optimize the 3D U-Net architecture for dose prediction in lung cancer radiation therapy (RT) plans, particularly in scenarios with limited clinical data, as well as to quan...
Authors: Blessing Akinro, Soumyanil Banerjee, Ming Dong, Carri K. Glide-Hurst, Prashant Nagpal, Chase Ruff, Nicholas R. Summerfield, Timothy P. Szczykutowicz
Affiliation: Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Departments of Radiology and Medical Physics, University Wisconsin-Madison, Department of Radiology, University of Wisconsin-Madison, Department of Computer Science, Wayne State University, Department of Human Oncology
Abstract Preview: Purpose: Radiation dose to coronary arteries (CAs) during thoracic radiotherapy (RT) is linked to cardiotoxicity. However, precise CA delineation for avoidance is limited by image quality and CA compl...
Authors: Maria Jose Medrano, Grant Stevens, Liyan Sun, Justin Ruey Tse, Adam S. Wang, Sen Wang
Affiliation: Department of Radiology, Stanford University, GE HealthCare, Stanford University
Abstract Preview: Purpose: Patient exposure to ionizing radiation is a major concern in CT imaging. Size-specific dose estimation methods can prospectively estimate organ-level radiation doses based on patient sizes an...
Authors: Daisuke Kawahara, Takaaki Matsuura, Yuji Murakami, Ryunosuke Yanagida
Affiliation: Hiroshima High-Precision Radiotherapy Cancer Center, Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Department of Radiation Oncology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima
Abstract Preview: Purpose: In recent years, automation in radiation therapy planning using AI has gained significant attention to reduce the workload of treatment planners. Adaptive Radiation Therapy (ART), as a new fo...
Authors: Petr Bruza, David J. Gladstone, Lesley A Jarvis, Austin Sloop, Kevin J. Willy, Rongxiao Zhang
Affiliation: Thayer School of Engineering, Dartmouth College, Dartmouth Cancer Center, Dartmouth Health
Abstract Preview: Purpose:
Active beam monitoring and output-gated dosimetry are essential systems for safe and accurate radiation delivery. UHDR irradiators such as the Mobetron rely on pre-programmed regimes and t...
Authors: Hilary Louisa Byrne, Paul J. Keall, John Kipritidis, Jeremy Lim
Affiliation: Northern Sydney Cancer Centre, University of Sydney, Image X Institute, Faculty of Medicine and Health, The University of Sydney
Abstract Preview: Purpose:
Non-contrast CT ventilation imaging (CTVI) has been developed as a cost-effective and accessible alternative to PET/SPECT V/Q imaging for visualizing lung function. However, the sensitivit...
Authors: Matthew Brown, Yushi Chang, Jinhyuk Choi, William Silva Mendes, Lei Ren, Aman Sangal, William Paul Segars, Phuoc Tran, Hualiang Zhong
Affiliation: University of Maryland School of Medicine, Department of Radiation Oncology, University of Maryland School of Medicine, Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center, Department of Radiation Oncology, Medical College of Wisconsin
Abstract Preview: Purpose: Digital phantoms like XCAT are essential for imaging and treatment optimization in radiology and radiation oncology. However, the lack of realistic textures (HU distribution) in XCAT limits i...
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 ...
Authors: Lori Buchholtz, Alison Garda, Chris L. Hallemeier, Kathryn L. Kolsky, Han Liu, Joseph John Lucido, Marisa Schinter, Andrew J. Veres, Sara Walerak
Affiliation: Mayo Clinic
Abstract Preview: Purpose: The C_START initiative aims to streamline and simplify the Direct-to-Unit (DtU) clinical setup and treatment planning process for photon radiation therapy, particularly for emergent cases suc...
Authors: Huixiao Chen, Zhe (Jay) Chen, MinYoung Lee, Sameer Taneja
Affiliation: Yale School of Medicine, Department of Therapeutic Radiology, Yale University School of Medicine
Abstract Preview: Purpose: Superficial radiation therapy uses low-energy x-rays to treat various types of cancers, including non-melanoma skin cancers, and dermatological conditions such as keloid scars, mycosis fungoi...
Authors: Hoyeon Lee
Affiliation: University of Hong Kong
Abstract Preview: Purpose: Deep-learning approaches are widely investigated for Cone-Beam CT (CBCT) scatter correction to improve the quality of the linear-accelerator mounted CBCT. This study aims to optimize the deep...
Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Kangning Zhang
Affiliation: 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:
This work demonstrates how existing software, when creatively adapted, can address a wide range of clinical challenges. By focusing on data exploration and application-specific modificatio...
Authors: Daniela Branco, John M Bryant, Shalom Kpetsu, Ann T. Nguyen, Gage H. Redler, Peter Allan Sandwall, Eman Suliman, Charles R. Thomas, Joseph Weygand
Affiliation: Department of Radiation Oncology and Applied Science, Dartmouth Health, University of South Florida Morsani College of Medicine, Alzahraa University Hospital, Dartmouth College, Moffitt Cancer Center, OhioHealth, Purdue University, University of California San Diego / California Protons, Department of Radiation Oncology, Moffitt Cancer Center
Abstract Preview: Purpose: Access to radiological health services in sub-Saharan Africa (sSA) remains extremely inadequate, with over 90% of the population in most countries lacking access to radiotherapy and facing si...
Authors: Kevin Peter Risolo
Affiliation: University of Pennsylvania
Abstract Preview: Purpose: To quantify the improved efficiency of checking patient treatment plan MU by utilizing RadFormationâs ClearCalc script-based program.
Methods: A total of 58 patients planned for treatment ...
Authors: Nuraddeen Nasiru Garba, Kalpana M Kanal, Abdullahi Mohammed, Rabiu Nasiru, Muhammad SHAFIU Shehu, Daniel Vergara, Joseph Everett Wishart
Affiliation: AHMADU BELLO UNIVERSITY, ZARIA, University of Washington
Abstract Preview: Purpose: To establish local Diagnostic Reference Levels (DRLs) for head and neck computed tomography (CT) exams in Abuja, Nigeria, and to investigate the performance of brain metastasis (BM) and brain...
Authors: Hongyu Jiang
Affiliation: Department of Radiation Oncology, University of Kansas Medical Center
Abstract Preview: Purpose: This study presents a method for transforming coordinates from RayStationâs treatment planning system into the Monte Carlo (MC) coordinate system used in GEANT4 for dose calculations in spot ...
Authors: Jing Qian, Brandon Reber, David M. Routman, Satomi Shiraishi
Affiliation: Mayo Clinic
Abstract Preview: Purpose: The dose distribution in proton radiotherapy (PRT) is characterized by sharp gradients, posing a challenge for machine learning-based dose prediction. While denoising with diffusion processes...
Authors: Guangjun Li, Ying Song, Huanan Tang, Tianxiong Wu, Qiuyi Ye, Wei Zhang
Affiliation: West China Second Hospital of Sichuan University, United Imaging Healthcare, West China Hospital of Sichuan University
Abstract Preview: Purpose:
To propose a general low-dose reconstruction model for ultra-sparse-view cone-beam CT (CBCT) and evaluate its clinical application in improving image quality and reducing radiation dose fo...
Authors: Laura I. Cervino, Wendy B. Harris, Paulo Quintero, Hao Zhang
Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center
Abstract Preview: Purpose: To evaluate the impact of the prediction uncertainty from CBCT-based synthetic CT (sCT) generation in abdominal adaptive radiotherapy.
Methods: CT and CBCT images from 65 abdominal pat...
Authors: Yunxiang Li, Weiguo Lu, Xiaoxue Qian, Hua-Chieh Shao, You Zhang
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
Abstract Preview: Purpose:
Curating high-quality, labeled data for medical image segmentation can be challenging and costly, considering the existence of various image domains with differing modalities/protocols. Cr...
Authors: Mingli Chen, Xuejun Gu, Hao Jiang, Mahdieh Kazemimoghadam, Weiguo Lu, Qingying Wang, Kangning Zhang
Affiliation: 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:
Converting MR images to synthetic CT (MR2sCT) is highly desirable as it streamlines the radiotherapy treatment planning workflow. This approach leverages the superior soft tissue visibilit...