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Results for "glioma mri": 12 found

12 Year Clinical Experience with Low-Tesla MRI for Tumor Progression

Authors: Soon N. Huh, Perry B. Johnson, Jiyeon Park, Ryan Stevens

Affiliation: University of Florida Health Proton Therapy Institute, UF Health Proton Therapy Institute, UFHPTI

Abstract Preview: Purpose:
Low-Tesla MRI (0.23T Panorama MR Scanner, Philips) has been used for tumor progression during proton therapy treatments, and for initial contouring in addition to diagnostic MRI. The pulse...

3D Bioprinted Brain Cancer Constructs for Experimental Synchrotron Radiotherapy

Authors: John Paul Ortiz Bustillo, Elette Engels, Elrick T. Inocencio, Michael Lerch, Julia Rebecca D Posadas, Anatoly Rosenfeld, Kiarn Roughley, Moeava Tehei, Gordon Wallace, Danielle Warren, Vincent de Rover

Affiliation: Centre for Medical Radiation Physics, University of Wollongong Australia, Department of Radiology, University of the Philippines- Philippine General Hospital, Intelligent Polymer Research Institute, ARC Centre of Excellence for Electromaterials Science, AIIM Facility, University of Wollongong Australia, Centre for Medical Radiation Physics, University of Wollongong, Intelligent Polymer Research Institute, ARC Centre of Excellence for Electromaterials Science, AIIM Facility, University of Wollongong, University of the Philippines Manila; Centre for Medical Radiation Physics, University of Wollongong Australia

Abstract Preview: Purpose: To compare the biological response through cell viability assay and fluorescence imaging of 3D bioprinted brain cancer (glioma) constructs relative to 2D monolayer and 3D spheroid culture for...

A Retrospective Assessment of Proton Radiation Response in Brain Tumor Patients Using Diffusion-Weighted MR Imaging

Authors: Liu Hong, Wen C. Hsi, Faraz Kalantari, Romy Megahed, Ganesh Narayanasamy, Maida Ranjbar, Pouya Sabouri, Zhong Su

Affiliation: University of Arkansas for Medical Sciences, Department of Radiation Oncology, University of Arkansas for Medical Sciences (UAMS)

Abstract Preview: Purpose: Quantitative apparent diffusion coefficients (ADC) in diffusion-weighted MRI (dMRI) reflect water diffusivity and thus provide tissue cellular density information. Functional diffusion mappin...

A Vision-Language Model for T1-Contrast Enhanced MRI Generation for Glioma Patients

Authors: Zachary Buchwald, Zach Eidex, Richard L.J. Qiu, Justin R. Roper, Mojtaba Safari, Hui-Kuo Shu, Xiaofeng Yang, David Yu

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

Abstract Preview: Purpose: Gadolinium-based contrast agents (GBCA) are commonly used for patients with gliomas to delineate and characterize the brain tumors using T1-weighted (T1W) MRI. However, there is a rising conc...

Addressing Missing MRI Sequences: A DL-Based Region-Focused Multi-Sequence Framework for Synthetic Image Generation

Authors: Amir Abdollahi, Oliver JΓ€kel, Maxmillian Knoll, Rakshana Murugan, Adithya Raman, Patrick Salome

Affiliation: UKHD & DKFZ, Department of Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ), German Cancer Research Centre(DKFZ), DKFZ, MGH

Abstract Preview: Purpose:
Missing MRI sequences, due to technical issues in data handling or clinical constraints like contrast agent intolerance, limit the use of medical imaging datasets in computational analysis...

Assessing the Risks of Synthetic MRI Data in Deep Learning: A Study on U-Net Segmentation Accuracy

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...

Deep Learning-Based Categorization of Brain Tumours Using Brain MRI : Advancing Precision Medicine in Neuroimaging

Authors: William F.B Igoniye, Belema Manuel, Christopher F. Njeh, O Ray-offor

Affiliation: Indiana University School of Medicine, Department of Radiation Oncology, Department of Radiology, University of Port Harcourt Teaching Hospital

Abstract Preview: Purpose: The accurate and efficient categorization of brain tumors is essential for effective treatment planning and improved patient outcomes. Current MRI-based diagnostic methods are time-intensive ...

Deep Learning-Driven Comparative Analysis of CNN-Based Architectures and High-Order Vision Mamba U-Net (H-vMUNet) for MRI-Based Brain Tumor Segmentation

Authors: Sang Hee Ahn, Nalee Kim, Do Hoon Lim

Affiliation: Samsung Medical Center, Department of Radiation Oncology, Samsung Medical Center, Sungkyunkwan University School of Medicine

Abstract Preview: Purpose: MRI offers superior soft-tissue contrast, aiding tumor localization and segmentation in radiation therapy, which traditionally relies on oncologists' expertise. This study compares CNN-based ...

Dose Dependent White Matter Injuries Quantified By Axial and Radial Diffusivity of Diffusion Tensor Imaging Significantly Correlate with Radiation-Induced Neurocognitive Decline in Diffuse Glioma Patients Underwent Chemoradiation Therapy

Authors: Robert Fucetola, Jiayi Huang, Zhihua Liu, Chongliang Luo, Tong Zhu

Affiliation: Washington University School of Medicine, Washington University in St. Louis, School of Medicine

Abstract Preview: Purpose:
This prospective observational study investigates radiation-induced white matter (WM) injuries using longitudinal diffusion tensor imaging (DTI) in patients with diffuse glioma following r...

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...

Research on Glioma MRI Image Generation Based on Large Language Model and Diffusion Model

Authors: Xiangli Cui, Chi Han, Man Hu, Wanli Huo, Xunan Wang, Jianguang Zhang, Yingying Zhang

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

Abstract Preview: Purpose:
Medical image generation has broad application prospects in deep learning, but the model training effect is often limited due to the lack of real image data. This study aims to explore the...

Spherical Slicing and Convolutions for Accurate Glioma Tumor Segmentation Using Multi-Parametric MRI

Authors: Ke Lu, Chunhao Wang, Ruoxu Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Lei Zhang, Rihui Zhang, Jingtong Zhao, Haiming Zhu

Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: The human brain’s spherical geometry offers unique opportunities for improving the segmentation of tiny and irregular anatomical structures. We hypothesize that representing the brain in sphe...