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Head and Neck Tumor Segmentation: First Challenge, Hecktor 2020, Held in Conjunction with Miccai 2020, Lima, Peru, October 4, 2020, Proceedings

Head and Neck Tumor Segmentation: First Challenge, Hecktor 2020, Held in Conjunction with Miccai 2020, Lima, Peru, October 4, 2020, Proceedings (Paperback, 2021)

Adrien Depeursinge, Vincent Andrearczyk, Valentin Oreiller (엮은이)
  |  
Springer
2021-01-13
  |  
93,100원

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Head and Neck Tumor Segmentation: First Challenge, Hecktor 2020, Held in Conjunction with Miccai 2020, Lima, Peru, October 4, 2020, Proceedings

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· 제목 : Head and Neck Tumor Segmentation: First Challenge, Hecktor 2020, Held in Conjunction with Miccai 2020, Lima, Peru, October 4, 2020, Proceedings (Paperback, 2021) 
· 분류 : 외국도서 > 컴퓨터 > 컴퓨터 비전/패턴 인식
· ISBN : 9783030671938
· 쪽수 : 109쪽

목차

Overview of the HECKTOR Challenge at MICCAI 2020: Automatic Head and Neck Tumor Segmentation in PET/CT.- Two-stage approach for segmenting gross tumor volume in head and neck cancer with CT and PET imaging.- The Head and Neck Tumor Segmentation Using nnU-Net with Spatial and Channel 'Squeeze & Excitation' Blocks.- Squeeze-and-Excitation Normalization for Automated Delineation of Head and Neck Primary Tumors in Combined PET and CT Images.- Automatic Head and Neck Tumor Segmentation in PET/CT with Scale Attention Network.- Iteratively Refine the Segmentation of Head and Neck Tumor in FDG-PET and CT images.- Combining CNN and Hybrid Active Contours for Head and Neck Tumor Segmentation in CT and PET images.- Oropharyngeal Tumour Segmentation using Ensemble 3D PET-CT Fusion Networks for the HECKTOR Challenge.- Patch-based 3D UNet for Head and Neck Tumor Segmentation with an Ensemble of Conventional and Dilated Convolutions.- Tumor Segmentation in Patients with Head and Neck Cancers using Deep Learning based-on Multi-modality PET/CT Images.- GAN-based Bi-modal Segmentation using Mumford-Shah Loss: Application to Head and Neck Tumors in PET-CT Images.

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