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Results for "component statistical": 4 found

A No-Reference Medical Image Quality Assessment Method Based on Automated Distortion Recognition Technology: Application to Preprocessing in MRI-Guided Radiotherapy

Authors: Jiayun Chen, Shengqi Chen, Yuan Tang, Zilin Wang, Guohua Wu, Jianan Wu

Affiliation: Cancer Hospital Chinese Academy of Medical Sciences, Shenzhen Center, School of Electronic Engineering, Beijing University of Posts and Telecommunications, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose:
To develop a novel no-reference image quality assessment (NRIQA) method for evaluating the effectiveness of image preprocessing in MRI-guided radiotherapy (MRIgRT), thereby enhancing clini...

A Novel Sphere Packing Solution Via Principal Component Analysis for Lattice SFRT Treatment of Large, Bulky, and Unresectable Tumors

Authors: James Robert Castle, Joshua Misa, Damodar Pokhrel, William St. Clair

Affiliation: University of Kentucky, Department of Radiation Medicine

Abstract Preview: Purpose: We propose a novel methodology for lattice deployment in spatially fractionated radiotherapy (SFRT), using principal component analysis (PCA) to improve sphere packing within the tumor. Impro...

An Adjustable Wool Fiber Phantom for Investigating the Detection of Anisotropy with Ultrasound Speckle Statistics

Authors: Alexandra Christensen, Timothy J. Hall, Ivan M. Rosado-Mendez

Affiliation: University of Wisconsin, Madison, Departments of Medical Physics and Radiology, University of Wisconsin-Madison

Abstract Preview: Purpose: Quantitative ultrasound techniques based on the statistical analysis of speckle are currently being deployed commercially and clinically as sources of biomarkers associated with tissue micros...

Development and Validation of a Principal Component Analysis Statistical Shape Pediatric/Adolescent Breast Model for Pre-CT Era Breast Dose Reconstruction in Late Effect Studies of Female Childhood Cancer Survivors

Authors: Gregory T. Armstrong, James E. Bates, Kristy K. Brock, Laurence Edward Court, Matt Ehrhardt, Danielle Friedman, Aashish C. Gupta, Donald Hancock, Rebecca M. Howell, Cindy Im, Tera S Jones, Choonsik Lee, Wendy Leisenring, Taylor Meyers, Lindsay Morton, Chaya Moskowitz, Joe Neglia, Vikki Nolan, Caleb O'Connor, Kevin C. Oeffinger, Constance A. Owens, Arnold C. Paulino, Chelsea C. Pinnix, Sander Roberti, Cecile Ronckers, Susan A. Smith, Kumar Srivastava, Lucie Turcotte

Affiliation: Department of Medicine, Duke University School of Medicine, Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, The University of Texas MD Anderson Cancer Center, Department of Oncology, St. Jude Children’s Research Hospital, Department of Pediatrics, Memorial Sloan Kettering Cancer Center, Division of Pediatric Epidemiology and Clinical Research, University of Minnesota, Division of Childhood Cancer Epidemiology, University Medicine at Johannes Gutenberg University Mainz, Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Department of Pediatrics, University of Minnesota, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Department of Biostatistics, St. Jude Children’s Research Hospital, Clinical Research Division, Fred Hutchinson Cancer Center, Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology and Winship Cancer Institute, Emory University, The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences

Abstract Preview: Purpose: To (1) develop and validate a novel anatomically realistic pediatric/adolescent population-based breast model, (2) incorporate model into an age-scalable female reference phantom, and (3) dem...