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Results for "mri dbt": 15 found

A Multimodal CAD System for Breast Cancer Detection: Integrating MRI, DBT, and Mammography for Dense Breast Challenges

Authors: Si-Wa Chan, Yuan-Yu Lee, Zhi-Ying Li, Jia-Wei Liao, Hui-Yu Cathy Tsai

Affiliation: Department of Radiology, Taichung Veterans General Hospital​, Institute of Nuclear Engineering and Science, National Tsing Hua University

Abstract Preview: Purpose: Dense breast tissue reduces the sensitivity of mammography, posing diagnostic challenges, especially for Asian women with high breast density (up to 50%). Current single-modality techniques o...

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...

Automatic Tumor Segmentation and Catheter Detection from MRI for Cervical Cancer Brachytherapy Using Uncertainty-Aware Dual Convolution-Transformer Unet

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...

BEST IN PHYSICS IMAGING: Cross-Contrast Diffusion: A Synergistic Approach for Simultaneous Multi-Contrast MRI Super-Resolution

Authors: Yifei Hao, Wenxuan Li, Xiang Li, Tao Peng, Yulu Wu, Fang-Fang Yin, Yue Yuan, Lei Zhang, Yaogong Zhang

Affiliation: Duke University, School of Future Science and Engineering, Soochow University, Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Diffusion-based deep-learning frameworks have been recently used in MRI resolution enhancement, or super-resolution. Multi-contrast MRI share common anatomical structures while holding comple...

Comparison of Optimized Magnetic Resonance Sequences in the Treatment Planning of Surface Brachytherapy

Authors: Ivan M. Buzurovic, Phillip M. Devlin, Evangelia Kaza, Michael John Lavelle

Affiliation: Department of Radiation Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Brigham and Women's Hospital, Harvard Medial School, Dana-Farber Cancer Institute, Department of Radiation Oncology

Abstract Preview: Purpose: Recent work in surface brachytherapy (SBT) has demonstrated the feasibility of using magnetic resonance (MR)-guidance in place of Computer Tomography (CT) in SBT planning. The purpose of this...

Feasibility Study of Deep Learning-Based MRI-to-PET Generation for Rectal Cancer: Overall Survival Prediction and Pathological Complete Response Assessment

Authors: Weigang Hu, Zhenhao Li, Jiazhou Wang, Xiaojie Yin, Zhen Zhang

Affiliation: Fudan University Shanghai Cancer Center

Abstract Preview: Purpose:
This study aims to develop and validate a novel deep learning method to generate synthetic PET images for rectal cancer from MRI data. By incorporating metabolic information from the synth...

Frequent MR Imaging of Fibrosis during Radiation Therapy: Implications for Adaptive RT in Gynecologic Cancer

Authors: Himanshu Bhat, Bruce Lewis Daniel, Junghoon Lee, Michael B. Roumeliotis, Ehud J. Schmidt, Ravi Seethamraju, Khadija Sheikh, Pan Su, Akila N. Viswanathan

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Siemens Medical Solutions USA Inc., Stanford Medical School, Department of Cardiology, Johns Hopkins University

Abstract Preview: Purpose: To perform frequent MRI during EBRT and brachytherapy (BT) to evaluate RT-induced fibrosis and remnant tumor changes, identified using ultrashort echo-time (UTE) and multiparametric (mpMRI), ...

From Noisy Signals to Accurate Maps: Transforming Look-Locker MRI with an Intelligent T₁ Estimation

Authors: Prabhu C. Acharya, Hassan Bagher-Ebadian, Stephen L. Brown, James R. Ewing, Mohammad M. Ghassemi, Benjamin Movsas, Farzan Siddiqui, Kundan S Thind

Affiliation: Michigan State University, Oakland University, Henry Ford Health

Abstract Preview: Purpose: Accurate T1 quantification using T One by Multiple Read Out Pulse (TOMROP) sequences is essential for physiological assessments in dynamic-contrast-enhanced (DCE) MRI and T1 mapping studies. ...

Generating 3D Brain in Volume (BRAVO) Images Using Attention-Gated Conditional Gan (AGC-GAN)

Authors: Nan Li, Shouping Xu, Gaolong Zhang, Xuerong Zhang

Affiliation: Department of Radiation Oncology, HeBei YiZhou proton center, School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College

Abstract Preview: Purpose:
The 3D BRAVO sequence is an advanced magnetic resonance (MR) technique that allows for image reconstruction at any angle. It offers 1 mm gapless scanning and has a high signal-to-noise rat...

Integrated Catheter Position and Dwell Time Optimization for Focal Dose Escalation in Prostate HDR Brachytherapy

Authors: Bryan Bednarz, John M. Floberg, Joseph B. Schulz, Jordan M. Slagowski

Affiliation: Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin - Madison, Department of Radiation Oncology, Stanford University School of Medicine, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: Catheter placement for high-dose-rate brachytherapy (HDR BT) is clinician dependent and potentially suboptimal for delivering simultaneous integrated boosts to intraprostatic gross tumor volu...

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...

Rapid Reconstruction of Extremely Accelerated Liver 4D MRI Via Chained Iterative Refinement

Authors: Mary Feng, Yi Lao, Hui Lin, Hengjie Liu, Xin Miao, Michael Ohliger

Affiliation: University of California, Los Angeles, Department of Radiation Oncology, University of California San Francisco, Department of Radiation Oncology, City of Hope National Medical Center, University of California San Francisco, Siemens Medical Solutions USA Inc.

Abstract Preview: Purpose: 4D MRI with high spatiotemporal resolution is vital to characterize the tumor/tumor motion for liver radiotherapy. However, high-quality 4D MRI requires an impractically long scanning time fo...

Retrospective MRI-Based Investigation of Bulboclitoris and Vaginal Canal Morphological and Physiological Changes in GYN Patients Treated with External Beam Radiation Therapy

Authors: Diandra Ayala-Peacock, Junzo Chino, Oana I. Craciunescu, Allison Jones, Kyle J. Lafata, Kim Light, Sheridan G. Meltsner, Jack B Stevens

Affiliation: Duke University, Department of Radiation Oncology, Duke University, Duke University Medical Center

Abstract Preview: Purpose: This study aims to develop an MR-based method that retrospectively correlates longitudinal changes in morphology and physiology for the bulboclitoris and vaginal canal with dose received duri...

Small but Mighty: A Lightweight and Computationally Efficient Model for Deformable Image Registration

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 ...

Using Multiple Sequences MRI for Synthesizing CT Based on a Deep Learning Approach

Authors: Jie Hu, Nan Li, Chuanbin Xie, Shouping Xu, Xinlei Xu, Gaolong Zhang, Zhilei Zhang

Affiliation: School of Physics, Beihang University, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Department of Radiation Oncology, the First Medical Center of the People's Liberation Army General Hospital, National Cancer Center/ National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, Peopleʼs Republic of China, Department of Radiation Oncology, School of Physics, Beihang University, Beijing, 102206, Peopleʼs Republic of China

Abstract Preview: Purpose: This study aims to synthesize CT images for MRI-only radiation therapy using a deep learning approach that integrates information from the T1- and T2-weighted MRI sequence.
Methods: 97 hea...