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Results for "knowledge map": 14 found

Analysis of the Accuracy of Avatar-Based Patient Positioning Technique for Radiation Therapy

Authors: Danna Gurari, Moyed Miften, Sarah Milgrom, Atharva Rajesh Peshkar, Willem Schreuder, David H. Thomas

Affiliation: University of Colorado Boulder, University of Colorado School of Medicine, University of Colorado Anschutz, Thomas Jefferson University

Abstract Preview: Purpose: To evaluate the accuracy of a novel avatar-based patient positioning technique.

Methods: We developed a modified surface-guided radiation therapy (SGRT) technique, 'Avatar-Guided Radia...

Comparative Evaluation of Nn-Unet Models for Radiotherapy Dose Prediction Using the Head and Neck Cancer Patients

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)...

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...

Development of a Knowledge-Based Planning Model for Optimal Trade-Off Guidance in Locally Advanced Non-Small Cell Lung Cancer

Authors: Ming Chao, Hao Guo, Tenzin Kunkyab, Yang Lei, Tian Liu, Kenneth Rosenzweig, Robert Samstein, James Tam, Junyi Xia, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai

Abstract Preview: Purpose:
The aim of the study is to develop a trade-off prediction model to efficiently guide the treatment planning process for patients with stage III non-small cell lung cancer (NSCLC).
Metho...

Empowered By Artificial Intelligence and Knowledge Map in Bio-Medical Physics Course

Authors: Jia Jing, Hui Lin, Daming Meng, Zhenyu Xiong

Affiliation: School of Physics, Hefei University of Technology, Rutgers Cancer Institute of New Jersey

Abstract Preview: Purpose: Artificial intelligence (AI) is attempting to understand the essence of intelligence and produce a new type of intelligent machine that can respond in a way similar to human intelligence. AI ...

Fine-Tuning AI-Based Generative Models for Small-Sample Glioma MRI Generation.

Authors: Xiangli Cui, Chunyan Fu, Man Hu, Wanli Huo, Jingyu Liu, Jianguang Zhang, Yingying Zhang, Shanyang Zhao

Affiliation: Institute of Health and Medical Technology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University, Departments of Radiation Oncology, Zibo Wanjie Cancer Hospital, Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, Department of Oncology, Xiangya Hospital, Central South University, College of Information Engineering, China Jiliang University, Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University, Shandong Academy of Medical Sciences

Abstract Preview: Purpose: To quantify the impact of fine-tuning strategies for pre-trained AI image generation models on glioma MRI image quality and observer performance, and to determine the optimal fine-tuning conf...

Impact of Transfer Learning on Estimation of Intravoxel Incoherent Motion Parameters in the Liver

Authors: Marissa Brown, Geoffrey D. Clarke, Luke Norton

Affiliation: University of Texas Health Science Center at San Antonio

Abstract Preview: Purpose: To evaluate how different learning strategies affect convolutional neural network (CNN) estimates of the liver's intravoxel incoherent motion (IVIM) parameters.
Methods: A 3-stage U-Net wa...

Improved SNR and Estimation Accuracy for Deuterium-MRI Acquired with Chemical Shift Imaging at 7 Tesla

Authors: Muhammed AR Anjum, Andrew J. Fagan

Affiliation: Mayo Clinic

Abstract Preview: Purpose:
This study describes a novel post-processing method to boost image SNR for deuterium-MRI acquired using chemical shift imaging (CSI) at 7T. Deuterium MRI via exogenous administration of a ...

Integrating Clinical Knowledge Via Llms for Precise Organ-at-Risk Segmentation in Pancreatic Cancer SBRT

Authors: Karyn A Goodman, Yang Lei, Tian Liu, Pretesh Patel, Jing Wang, Kaida Yang, Jiahan Zhang

Affiliation: Icahn School of Medicine at Mount Sinai, Department of Radiation Oncology and Winship Cancer Institute, Emory University

Abstract Preview: Purpose: This study aims to improve organ-at-risk (OAR) segmentation in pancreatic cancer stereotactic body radiotherapy (SBRT) by integrating clinical guidelines into deep learning workflows. We use ...

Integrating Neuroanatomic Knowledge in Clinical Target Volumes for Glioma Patients Using Deep Learning

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...

Knowledge-Based Deep Residual U-Net for Synthetic CT Generation Using a Single MR Volume for Frameless Radiosurgery

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...

Knowledge-Based Three-Dimensional Dose Prediction for High Dose Rate Prostate Brachytherapy

Authors: Mojtaba Behzadipour, Suman Gautam, Tianjun Ma, Ikchit Singh Sangha, Bongyong Song, William Song, Kumari Sunidhi

Affiliation: UC San Diego, Virginia Commonwealth University

Abstract Preview: Purpose: This study aims to develop a knowledge-based voxel-wise dose prediction system using a convolutional neural network (CNN) for high-dose-rate (HDR) prostate brachytherapy and to evaluate its p...

Knowledge-Informed Deep Learning for Accurate and Interpretable Extracapsular Extension Detection in Head and Neck Squamous Cell Carcinoma

Authors: William N. Duggar, Amirhossein Eskorouchi, Haifeng Wang

Affiliation: Mississippi State University, University of Mississippi Medical Center

Abstract Preview: Purpose:
Extracapsular extension (ECE) in lymph nodes represents a critical prognostic factor in head and neck squamous cell carcinoma (HNSCC), bearing important implications for staging, treatment...

Physician-Centered Decision-Making Tool for Individualized Outcome-Based Treatment Planning

Authors: Soren Bentzen, Arezoo Modiri, Zaker Rana, Amit Sawant, Lena Specht, Ivan Vogelius

Affiliation: University of Maryland, University of Maryland in Baltimore, Dept. Of Oncology Copenhagen University Hospital – Rigshospitalet, Maryland University Baltimore, Department of Radiation Oncology, University of Maryland School of Medicine

Abstract Preview: Purpose: There is wide inter-physician radiotherapy planning variability for lymphomas and no systematic way to individualize a plan with respect to patient-specific outcome risks. In response to this...