同音 发表于 2025-3-25 13:45:02
http://reply.papertrans.cn/43/4246/424585/424585_23.pngMorsel 发表于 2025-3-25 19:31:02
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,Automated Head and Neck Tumor Segmentation from 3D PET/CT HECKTOR 2022 Challenge Report,ymph nodes from 3D CT and PET images. In this work, we describe our solution to HECKTOR 2022 segmentation task. We re-sample all images to a common resolution, crop around head and neck region, and train SegResNet semantic segmentation network from MONAI. We use 5-fold cross validation to select besalleviate 发表于 2025-3-26 03:55:10
,A Coarse-to-Fine Ensembling Framework for Head and Neck Tumor and Lymph Segmentation in CT and PET lay an important role but their manual segmentations are time-consuming and laborious. In this paper, we propose a coarse-to-fine ensembling framework to segment the H &N tumor and metastatic lymph nodes automatically from Positron Emission Tomography (PET) and Computed Tomography (CT) images. The f壮观的游行 发表于 2025-3-26 04:18:27
A General Web-Based Platform for Automatic Delineation of Head and Neck Gross Tumor Volumes in PET/ntation method for head and neck primary and nodal gross tumor volumes (GTVp and GTVn) segmentation in positron emission tomography/computed tomography (PET/CT) provided by the MICCAI 2022 Head and Neck Tumor Segmentation Challenge (HECKTOR 2022). Our segmentation algorithm takes nnU-Net as the backexcrete 发表于 2025-3-26 11:11:04
http://reply.papertrans.cn/43/4246/424585/424585_28.pngFEMUR 发表于 2025-3-26 13:16:08
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Fusion-Based Automated Segmentation in Head and Neck Cancer via Advance Deep Learning Techniques,when designing therapeutic strategies. We set to automatically segment HNSCC using advanced deep learning techniques linked to the image fusion technique.. 883 subjects were extracted from HECKTOR-Challenge. 524 subjects were considered for the training and validation procedure, and 359 subjects as祝贺 发表于 2025-3-26 23:17:04
,Stacking Feature Maps of Multi-scaled Medical Images in U-Net for 3D Head and Neck Tumor Segmentatihe medical domain, it remains as challenging tasks since medical data is heterogeneous, multi-level, and multi-scale. Head and Neck Tumor Segmentation Challenge (HECKTOR) provides a platform to apply machine learning techniques to the medical image domain. HECKTOR 2022 provides positron emission tom打包 发表于 2025-3-27 05:12:07
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