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Results for "brain substructures": 6 found

Foundation Models with Balanced Data Sampling Enhance Auto-Segmentation for Cardiac Substructures

Authors: Chloe Min Seo Choi, Nikhil Mankuzhy, Aneesh Rangnekar, Andreas Rimner, Maria Thor, Harini Veeraraghavan, Abraham Wu

Affiliation: Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: Cardiac substructure irradiation predisposes patients for poor outcomes in thoracic radiation therapy. A deep learning model was developed to segment the cardiac substructures invariant to co...

Improvements from Monte Carlo Simulations over Pencil Beam Algorithms for Normal Tissue Dose Reconstruction in Proton Therapy Patients

Authors: Amy Berrington de Gonzalez, Keith T Griffin, Jae Won Jung, Cari M Kitahara, Choonik Lee, Choonsik Lee, Aimee L McNamara, Matthew Mille, Harald Paganetti, Sergio Morato Rafet, Jan PO Schuemann, Jungwook Shin, Torunn I Yock

Affiliation: University of Michigan, East Carolina University, Massachusetts General Hospital, National Cancer Institute, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Massachusetts General Hospital and Harvard Medical School, Institute of Cancer Research

Abstract Preview: Purpose: Radiotherapy dose reconstruction enables retrospective epidemiological studies that connect late health effects to the organ-absorbed radiation doses received during treatment. Though clinica...

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...

Mask-Based Synthetic Contrast-Enhanced CT Generation for Advancing Data Limited Segmentation on Cardiac Substructure

Authors: Jin Sung Kim, Chanwoong Lee, Young Hun Yoon

Affiliation: Department of Radiation Oncology, Yonsei Cancer Center, Heavy Ion Therapy Research Institute, Yonsei University College of Medicine

Abstract Preview: Purpose: Chest contrast-enhanced CT (CECT) serves as a valuable tool for cardiac imaging, but its lack of detailed anatomical visualization limits its utility in segmentation tasks. While CECT offers ...

Modality-Agnostic Image Cascade (MAGIC) for Multi-Modality Cardiac Substructure Segmentation

Authors: Ming Dong, Carri K. Glide-Hurst, Qisheng He, Anudeep Kumar, Alex Singleton Kuo, Joshua Pan, Chase Ruff, Nicholas R. Summerfield

Affiliation: Department of Computer Science, Wayne State University, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: Recent evidence highlights the importance of incorporating cardiac substructures (CS) into treatment planning for thoracic cancers, however current segmentation methods are limited to a singl...

Spatially Informed Auto-Segmentation of Cardiac Nodes for Radiotherapy Treatment Planning

Authors: Ming Dong, Carri K. Glide-Hurst, Joshua Pan, Nicholas R. Summerfield

Affiliation: Department of Computer Science, Wayne State University, Departments of Human Oncology and Medical Physics, University of Wisconsin-Madison, Department of Human Oncology, University of Wisconsin-Madison

Abstract Preview: Purpose: Radiation dose to the cardiac nodes is more strongly associated with conduction disorders and arrythmias than whole heart (WH) metrics. However, node segmentation is challenging due to comple...