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Results for "domain generalization": 4 found

Incorporating Cyclic Group Equivariance into Deep Learning for Reliable Reconstruction of Rotationally Symmetric Tomography Systems

Authors: Fang-Fang Yin, Lei Zhang, Yaogong Zhang

Affiliation: Medical Physics Graduate Program, Duke Kunshan University

Abstract Preview: Purpose: Rotational symmetry is an inherent property of many tomography systems (e.g., CT, PET, SPECT), arising from the circular arrangement or rotation of detectors. This study revisits the image re...

Integrating Foundation Model with Self-Supervised Learning for Brain Lesion Segmentation with Multimodal and Diverse MRI Datasets

Authors: Zong Fan, Fan Lam, Hua Li, Rita Huan-Ting Peng, Yuan Yang

Affiliation: University of Illinois at Urbana Champaign, University of Illinois at Urbana-Champaign, Washington University School of Medicine, University of Illinois Urbana-Champaign

Abstract Preview: Purpose: Accurate lesion segmentation in MRI is critical for early diagnosis, treatment planning, and monitoring disease progression in various neurological disorders. Cross-site MRI data can alleviat...

Research on Multi-Organ Segmentation Based on Cross-Domain Transfer Learning

Authors: Jiali Gong, Yi Guo, Chi Han, Wanli Huo, Hongdong Liu, Zhao Peng, Yaping Qi, Zhaojuan Zhang

Affiliation: Department of Radiotherapy, cancer center, The First Affiliated Hospital of Fujian Medical University, Department of Oncology, Xiangya Hospital, Central South University, 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, China Jiliang University, Division of lonizing Radiation Metrology, National Institute of Metrology, Key Laboratory of Electromagnetic Wave Information Technology and Metrology of Zhejiang Province, College of Information Engineering, China Jiliang University, the Zhejiang-New Zealand Joint Vision-Based Intelligent Metrology Laboratory, College of Information Engineering, China Jiliang University

Abstract Preview: Purpose: To address overfitting from limited training data in multi-organ segmentation, an efficient transfer learning framework is proposed. It reduces reliance on training samples, enabling a single...

Segmentation Regularized Registration Training Improves Multi-Domain Generalization of Deformable Image Registration for MR-Guided Prostate Radiotherapy

Authors: Lando S. Bosma, Victoria Brennan, Nicolas Cote, ChengCheng Gui, Nima Hassan Rezaeian, Jue Jiang, Sudharsan Madhavan, Josiah Simeth, Neelam Tyagi, Harini Veeraraghavan, Michael J Zelefsky

Affiliation: Department of Medical Physics, Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, NYU Langone Health, University Medical Center Utrecht, Memorial Sloan Kettering Cancer Center

Abstract Preview: Purpose: Deep learning-based deformable image registration (DIR) models often lack robustness when applied to datasets with differing imaging characteristics. We aimed to (1) improve registration netw...