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Results for "predicting left": 6 found

A Novel Metric for Predicting Heart Dose Assessment in Left-Sided Breast Cancer Radiotherapy

Authors: Yufeng Cao, Arun Gopal, Kai Huang, Kai Wang

Affiliation: Department of Radiation Oncology, University of Maryland School of Medicine, Department of Radiation Oncology, University of Maryland Medical Center, University of Maryland, Baltimore

Abstract Preview: Purpose: The treatment of left-sided breast tumors poses significant concerns regarding the risk of radiation-induced damage to nearby organs, particularly the heart. In clinical practice, breath-hold...

Can Regional Radiomic Features from Pre-Treatment Computed Tomography Serve As Biomarkers for Predicting Radiation Pneumonitis?

Authors: David J. Carlson, Ming Chao, Tian Liu, Yong Hum Na, Kenneth E Rosenzweig, Robert Samstein, Lewis Tomalin

Affiliation: Icahn School of Medicine at Mount Sinai, Yale University School of Medicine, Department of Therapeutic Radiology, Yale University School of Medicine

Abstract Preview: Purpose: To investigate the potential of regional radiomic features extracted from five lung sub-lobes on pre-treatment CT as biomarkers for predicting radiation pneumonitis (RP) using machine learnin...

Dosemorph: A Study on Few-Shot Learning and Dose-Anatomy Registration for Radiotherapy Optimal Dose Prediction in Cervical Cancer

Authors: Xiance Jin

Affiliation: 1st Affiliated Hospital of Wenzhou Medical University

Abstract Preview: Purpose:
Deep learning deformable registration models was proposed to predict optimal dose distributions a with a few of optimal planned doses using a few-shot learning for cervical cancer.
Meth...

Enhancing Radiotherapy Planning with Machine Learning: Correlating Anatomical Features and Planning Difficulty to Guide Optimal Plan Design

Authors: Li Chen, Shouliang Ding, Xiaoyan Huang, Lecheng Jia, Hua Li, Hongdong Liu, Yanfei Liu, Zun Piao, Guangyu Wang

Affiliation: State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Shenzhen United Imaging Research Institute of Innovative Medical Equipment

Abstract Preview: Purpose: Optimal radiotherapy planning is challenging, influenced by anatomical factors such as surrounding organs and tumor characteristics, which complicate dose distribution and target coverage. Wh...

Inter-Machine Harmonization in Echocardiographic Videos for Predicting Left Ventricular Ejection Fraction

Authors: Akihiro Haga, Ren Iwasaki, Kenya Kusunose, Makoto Miyake, Kenji Moriuchi, Yasuharu Takeda, Hidekazu Tanaka, Hirotsugu Yamada

Affiliation: Department of Cardiovascular Medicine, Nephrology, and Neurology Graduate School of Medicine, University of the Ryukyus, Graduate School of Biomedical Sciences, Tokushima University, Tokushima university, Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine, Department of Cardiology, Tenri Hospital, Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine, Division of Heart Failure, Department of Heart Failure and Transplant, National Cerebral and Cardiovascular Center

Abstract Preview: Purpose: Device dependency is a significant challenge in medical AI, potentially limiting generalization performance. This study aimed to develop a robust deep learning model for predicting left ventr...

Predicting Elective Pelvic Nodal Volumes with Deep Learning: A Tool to Facilitate Peer Review

Authors: Brian M. Anderson, Shiva K. Das, Meagan Foster, Anirudh Karunaker, Lawrence B. Marks, Lukasz Mazur, Michael Repka

Affiliation: UNC Chapel HIll, University of North Carolina at Chapel Hill, UNC School of Medicine, University of North Carolina

Abstract Preview: Purpose: Development of a peer review segmentation check system to identify deviations in physician contours of standard risk pelvic lymph nodes in patients receiving radiation therapy for prostate an...