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: 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: ...
Authors: Wookjin Choi, Jun Li
Affiliation: Thomas Jefferson University
Abstract Preview: Purpose: Resin Yttrium-90 (Y-90) selective internal radiation therapy (SIRT) is a radioembolization procedure which uses Y-90 microspheres to treat metastatic liver cancer. In the procedure, liver vol...
Authors: John Ginn, Chenlu Qin, Deshan Yang
Affiliation: Duke University, Department of Radiation Oncology, Duke University
Abstract Preview: Purpose: Clinical implementation of auto-segmentation tools has been hindered by poor interpretability and generalizability of AI models, necessitating the development of automated contour quality ass...
Authors: Jin Sung Kim, Chanwoong Lee, Young Hun Yoon
Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine
Abstract Preview: Purpose: Chest contrast-enhanced CT (CECT) serves as a valuable tool for cardiac imaging, but its lack of detailed anatomical visualization limits its utility in segmentation tasks. While CECT offers ...
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: Wesley E. Bolch, Emily L. Marshall, Dhanashree Rajderkar, Wyatt Smither
Affiliation: University of Florida
Abstract Preview: Purpose: To determine the accuracy of TotalSegmentator, an AI-based automatic segmentation toolkit, on pediatric CT scans as the original software was trained on adult image datasets with a mean patie...
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: 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...
Authors: Klaus Bacher, Louise D'hondt, Jeff Rutten, Gwenny Verfaillie
Affiliation: Ghent University
Abstract Preview: Purpose: Manual organ segmentation is a very time-consuming but necessary process in personalized dosimetry. Automatic segmentation tools may alleviate this task. In this study the impact of automatic...