Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data (Record no. 186321)
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| 000 -LEADER | |
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| fixed length control field | 05644nam a22005895i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-030-71827-5 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240423130223.0 |
| 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 | 210312s2021 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783030718275 |
| -- | 978-3-030-71827-5 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-030-71827-5 |
| 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 | Segmentation, Classification, and Registration of Multi-modality Medical Imaging Data |
| Medium | [electronic resource] : |
| Remainder of title | MICCAI 2020 Challenges, ABCs 2020, L2R 2020, TN-SCUI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings / |
| Statement of responsibility, etc | edited by Nadya Shusharina, Mattias P. Heinrich, Ruobing Huang. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 1st ed. 2021. |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Springer, |
| -- | 2021. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XIX, 156 p. 57 illus., 54 illus. in color. |
| Other physical details | online resource. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | Image Processing, Computer Vision, Pattern Recognition, and Graphics, |
| International Standard Serial Number | 3004-9954 ; |
| Volume number/sequential designation | 12587 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | ABCs – Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images -- Cross-modality Brain Structures Image Segmentation for the Radiotherapy Target Definition and Plan Optimization -- Domain Knowledge Driven Multi-modal Segmentation of Anatomical Brain Barriers to Cancer Spread -- Ensembled ResUnet for Anatomical Brain Barriers Segmentation -- An Enhanced Coarse-to-_ne Framework for the segmentation of clinical target volume -- Automatic Segmentation of brain structures for treatment planning optimization and target volume definition -- A Bi-Directional, Multi-Modality Framework for Segmentation of Brain Structures -- L2R – Learn2Reg: Multitask and Multimodal 3D Medical Image Registration -- Large Deformation Image Registration with Anatomy-aware Laplacian Pyramid Networks -- Discrete Unsupervised 3D Registration Methods for the Learn2Reg Challenge -- Variable Fraunhofer MEVIS RegLib comprehensively applied to Learn2Reg Challenge -- Learning a deformable registration pyramid -- Deep learning based registration using spatial gradients and noisy segmentation labels -- Multi-step, Learning-based, Semi-supervised Image Registration Algorithm -- Using Elastix to register inhale/exhale intrasubject thorax CT: a unsupervised baseline to the task 2 of the Learn2Reg challenge -- TN-SCUI – Thyroid Nodule Segmentation and Classification in Ultrasound Images -- Cascade Unet and CH-Unet for thyroid nodule segmenation and benign and malignant classification -- Identifying Thyroid Nodules in Ultrasound Images through Segmentation-guided Discriminative Localization -- Cascaded Networks for Thyroid Nodule Diagnosis from Ultrasound Images -- Automatic Segmentation and Classification of Thyroid Nodules in Ultrasound Images with Convolutional Neural Networks -- LRTHR-Net: A Low-Resolution-to-High-Resolution Framework to Iteratively Refine the Segmentation of Thyroid Nodule in Ultrasound Images -- Coarse to Fine Ensemble Network for Thyroid Nodule Segmentation. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | This book constitutes three challenges that were held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020*: the Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images Challenge, the Learn2Reg Challenge, and the Thyroid Nodule Segmentation and Classification in Ultrasound Images Challenge. The 19 papers presented in this volume were carefully reviewed and selected form numerous submissions. The ABCs challenge aims to identify the best methods of segmenting brain structures that serve as barriers to the spread of brain cancers and structures to be spared from irradiation, for use in computer assisted target definition for glioma and radiotherapy plan optimization. The papers of the L2R challenge cover a wide spectrum of conventional and learning-based registration methods and often describe novel contributions. The main goal of the TN-SCUI challenge is tofind automatic algorithms to accurately segment and classify the thyroid nodules in ultrasound images. *The challenges took place virtually due to the COVID-19 pandemic. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Image processing |
| General subdivision | Digital techniques. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer vision. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial intelligence. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Bioinformatics. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer Imaging, Vision, Pattern Recognition and Graphics. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Artificial Intelligence. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computational and Systems Biology. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Shusharina, Nadya. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Heinrich, Mattias P. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Huang, Ruobing. |
| Relator term | editor. |
| Relator code | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer Nature eBook |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783030718268 |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783030718282 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Image Processing, Computer Vision, Pattern Recognition, and Graphics, |
| -- | 3004-9954 ; |
| Volume number/sequential designation | 12587 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="https://doi.org/10.1007/978-3-030-71827-5">https://doi.org/10.1007/978-3-030-71827-5</a> |
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| -- | ZDB-2-LNC |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | eBooks-CSE-Springer |
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