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Prior information guided deep-learning model for tumor bed segmentation . . . Incorporating the prior tumor contour information in the deep-learning model can effectively improve the segmentation accuracy of TB Comparing with Dai’s and Kazemimoghadam’s methods, the DSC of the proposed method increases with 28% and 6%, respectively
Prior information guided deep-learning model for tumor bed segmentation . . . To facilitate this process, a deep learning model is developed to segment TB from CT with the guidance of prior tumor location Initially, the tumor contour on the pre-operative CT is delineated by physician for surgical planning purpose
Prior information guided auto-segmentation of clinical target volume of . . . In this study the prior information was introduced to aid auto-segmentation of CTV-TB based on a deep-learning model To aid the delineation of CTV-TB, the tumor contour on preoperative CT was transformed onto postoperative CT via deformable image registration
Prior information guided auto-segmentation of clinical target volume of . . . In this study, a prior information guided deep-learning model was developed to automatically segment CTV-TB from postoperative CT The results showed that the introduction of prior information succeeded in identifying low-contrast CTV-TB from surrounding normal tissue on postoperative CT
Leveraging Prior Knowledge in a Hybrid Network for Multimodal Brain . . . Recent advancements in deep learning have significantly enhanced brain tumor segmentation from MRI data, providing valuable support for clinical diagnosis and treatment planning However, challenges persist in effectively integrating prior medical knowledge, capturing global multimodal features, and accurately delineating tumor boundaries To address these challenges, the Hybrid Network for
Shape prior-constrained deep learning network for medical image . . . In the testing stage, we propose a circular collaboration framework strategy which combines a shape generator auto-encoder network model with a segmentation network model, allowing the two models to collaborate with each other, resulting in a cooperative effect that leads to accurate segmentations
Prior information guided deep-learning model for tumor bed segmentation . . . To facilitate this process, a deep learning model is developed to segment TB from CT with the guidance of prior tumor location Initially, the tumor contour on the pre-operative CT is delineated by physician for surgical planning purpose