Head and Neck Tumor Segmentation and Outcome Prediction (Record no. 90448)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 06729nam a22006255i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-030-98253-9 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240730180658.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 220312s2022 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783030982539 |
| -- | 978-3-030-98253-9 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-030-98253-9 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | TA1501-1820 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | TA1634 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYT |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM016000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UYT |
| Source | thema |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006 |
| Edition number | 23 |
| 245 10 - TITLE STATEMENT | |
| Title | Head and Neck Tumor Segmentation and Outcome Prediction |
| Medium | [electronic resource] : |
| Remainder of title | Second Challenge, HECKTOR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings / |
| Statement of responsibility, etc. | edited by Vincent Andrearczyk, Valentin Oreiller, Mathieu Hatt, Adrien Depeursinge. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2022. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Cham : |
| Name of producer, publisher, distributor, manufacturer | Springer International Publishing : |
| -- | Imprint: Springer, |
| Date of production, publication, distribution, manufacture, or copyright notice | 2022. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | X, 328 p. 102 illus., 88 illus. in color. |
| Other physical details | online resource. |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type term | computer |
| Media type code | c |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | online resource |
| Carrier type code | cr |
| Source | rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS | |
| File type | text file |
| Encoding format | |
| Source | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | Lecture Notes in Computer Science, |
| International Standard Serial Number | 1611-3349 ; |
| Volume/sequential designation | 13209 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Overview of the HECKTOR Challenge at MICCAI 2021: Automatic -- Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT Images -- CCUT-Net: Pixel-wise Global Context Channel Attention UT-Net for head and neck tumor segmentation -- A Coarse-to-Fine Framework for Head and Neck Tumor Segmentation in CT and PET Images -- Automatic Segmentation of Head and Neck (H&N) Primary Tumors in PET and CT images using 3D-Inception-ResNet Model -- The Head and Neck Tumor Segmentation in PET/CT Based on Multi-channel Attention Network -- Multimodal Spatial Attention Network for Automatic Head and Neck Tumor Segmentation in FDG-PET and CT Images -- PET Normalizations to Improve Deep Learning Auto-Segmentation of Head and Neck Tumors in 3D PET/CT -- The Head and Neck Tumor Segmentation based on 3D U-Net: 3D U-net applied to Simple Attention Module for Head and Neck tumor segmentation in PET and CT images -- Skip-SCSE Multi-Scale Attention and Co-Learning method for Oropharyngeal Tumor Segmentation on multi-modal PET-CT images -- Head and Neck Cancer Primary Tumor Auto Segmentation using Model Ensembling of Deep Learning in PET/CT Images -- Priori and Posteriori Attention for Generalizing Head and Neck Tumors Segmentation -- Head and Neck Tumor Segmentation with Deeply-Supervised 3D UNet and Progression-Free Survival Prediction with Linear Model -- Deep learning based GTV delineation and progression free survival risk score prediction for head and neck cancer patients -- Multi-task Deep Learning for Joint Tumor Segmentation and Outcome Prediction in Head and Neck Cancer -- PET/CT Head and Neck tumor segmentation and Progression Free Survival prediction using Deep and Machine learning techniques -- Automatic Head and Neck Tumor Segmentation and Progression Free Survival Analysis on PET/CT images -- Multimodal PET/CT Tumour Segmentation and Progression-Free Survival Prediction using a Full-scale UNet with Attention -- Advanced Automatic Segmentation of Tumors and Survival Prediction in Head and Neck Cancer -- Fusion-Based head and neck Tumor Segmentation and Survival prediction using Robust Deep Learning Techniques and Advanced Hybrid Machine Learning Systems -- Head and Neck Primary Tumor Segmentation using Deep Neural Networks and Adaptive Ensembling -- Segmentation and Risk Score Prediction of Head and Neck Cancers in PET/CT Volumes with 3D U-Net and Cox Proportional Hazard Neural Networks -- Dual-Path Connected CNN for Tumor Segmentation of Combined PET-CT Images and Application to Survival Risk Prediction -- Deep Supervoxel Segmentation Survival Anaylsis in Head and Neck Cancer Patients -- A Hybrid Radiomics Approach to Modeling Progression-free Survival in Head and Neck Cancers -- An Ensemble Approach for Patient Prognosis of Head and Neck Tumor Using Multimodal Data -- Progression Free Survival Prediction for Head and Neck Cancer using Deep Learning based on Clinical and PET/CT Imaging Data -- Combining Tumor Segmentation Masks with PET/CT Images and Clinical Data in a Deep Learning Framework for Improved Prognostic Prediction in Head and Neck Squamous Cell Carcinoma -- Self-supervised multi-modality image feature extraction for the progression free survival prediction in head and neck cancer -- Comparing deep learning and conventional machine learning for outcome prediction of head and neck cancer in PET/CT. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | This book constitutes the Second 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021. The challenge took place virtually on September 27, 2021, due to the COVID-19 pandemic. The 29 contributions presented, as well as an overview paper, were carefully reviewed and selected form numerous submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 325 delineated PET/CT images was made available for training. . |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Image processing |
| General subdivision | Digital techniques. |
| 9 (RLIN) | 4145 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Computer vision. |
| 9 (RLIN) | 121335 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Education |
| General subdivision | Data processing. |
| 9 (RLIN) | 82607 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Application software. |
| 9 (RLIN) | 121336 |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Machine learning. |
| 9 (RLIN) | 1831 |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Computer Imaging, Vision, Pattern Recognition and Graphics. |
| 9 (RLIN) | 31569 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Computers and Education. |
| 9 (RLIN) | 41129 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Computer and Information Systems Applications. |
| 9 (RLIN) | 121337 |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Machine Learning. |
| 9 (RLIN) | 1831 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Andrearczyk, Vincent. |
| Relator term | editor. |
| Relationship | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 9 (RLIN) | 121338 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Oreiller, Valentin. |
| Relator term | editor. |
| Relationship | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 9 (RLIN) | 121339 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Hatt, Mathieu. |
| Relator term | editor. |
| Relationship | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 9 (RLIN) | 121340 |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Depeursinge, Adrien. |
| Relator term | editor. |
| Relationship | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 9 (RLIN) | 121341 |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 9 (RLIN) | 121342 |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer Nature eBook |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9783030982522 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Relationship information | Printed edition: |
| International Standard Book Number | 9783030982546 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Lecture Notes in Computer Science, |
| International Standard Serial Number | 1611-3349 ; |
| Volume/sequential designation | 13209 |
| 9 (RLIN) | 23263 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-3-030-98253-9">https://doi.org/10.1007/978-3-030-98253-9</a> |
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| -- | ZDB-2-SXCS |
| 912 ## - | |
| -- | ZDB-2-LNC |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks-Lecture Notes in CS |
No items available.