Del 12603 i serien Lecture Notes in Computer Science

Head and Neck Tumor Segmentation

First Challenge, HECKTOR 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings

Häftad, Engelska, 2021

AvVincent Andrearczyk,Valentin Oreiller,Adrien Depeursinge

699 kr

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This book constitutes the First 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020.

Produktinformation

Utgivningsdatum2021-01-13
Mått155 x 235 x 7 mm
Vikt195 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor109
FörlagSpringer Nature Switzerland AG
ISBN9783030671938

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Systemvetenskap och AI inom Data och IT
Programvaruutveckling inom Data och IT
Biovetenskap inom Naturvetenskap och teknik

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.