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View article: SynBT: High-quality Tumor Synthesis for Breast Tumor Segmentation by 3D Diffusion Model
SynBT: High-quality Tumor Synthesis for Breast Tumor Segmentation by 3D Diffusion Model Open
Synthetic tumors in medical images offer controllable characteristics that facilitate the training of machine learning models, leading to an improved segmentation performance. However, the existing methods of tumor synthesis yield suboptim…
View article: Comprehensive deep learning-based framework for automatic organs-at-risk segmentation in head-and-neck and pelvis for MR-guided radiation therapy planning
Comprehensive deep learning-based framework for automatic organs-at-risk segmentation in head-and-neck and pelvis for MR-guided radiation therapy planning Open
Introduction: The excellent soft-tissue contrast of magnetic resonance imaging (MRI) is appealing for delineation of organs-at-risk (OARs) as it is required for radiation therapy planning (RTP). In the last decade there has been an increas…
View article: Adaptable volumetric liver segmentation model for CT images using region-based features and convolutional neural network
Adaptable volumetric liver segmentation model for CT images using region-based features and convolutional neural network Open
Liver plays an important role in metabolic processes, therefore fast diagnosis and potential surgical planning is essential in case of any disease. The automatic liver segmentation approach has been studied during the past years and differ…
View article: Deep-Learning-based Segmentation of Organs-at-Risk in the Head for MR-assisted Radiation Therapy Planning
Deep-Learning-based Segmentation of Organs-at-Risk in the Head for MR-assisted Radiation Therapy Planning Open
Segmentation of organs-at-risk (OAR) in MR images has several clinical applications; including radiation therapy (RT) planning. This paper presents a deep-learning-based method to segment 15 structures in the head region. The proposed meth…