소장자료
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245 | 1 | 0 | ▼aCerebral Aneurysm Detection and Analysis▼h[electronic resource] :▼bFirst Challenge, CADA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings /▼cedited by Anja Hennemuth, Leonid Goubergrits, Matthias Ivantsits, Jan-Martin Kuhnigk.▲ |
250 | ▼a1st ed. 2021.▲ | ||
264 | 1 | ▼aCham :▼bSpringer International Publishing :▼bImprint: Springer,▼c2021.▲ | |
300 | ▼aX, 113 p. 47 illus., 41 illus. in color.▼bonline resource.▲ | ||
336 | ▼atext▼btxt▼2rdacontent▲ | ||
337 | ▼acomputer▼bc▼2rdamedia▲ | ||
338 | ▼aonline resource▼bcr▼2rdacarrier▲ | ||
347 | ▼atext file▼bPDF▼2rda▲ | ||
490 | 1 | ▼aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;▼v12643▲ | |
505 | 0 | ▼aOverview of the CADA Challenge at MICCAI 2020 -- Cerebral Aneurysm Detection and Analysis Challenge 2020 (CADA) -- Introduction -- CADA: Clinical Background and Motivation -- Cerebral Aneurysm Detection -- Deep Learning-Based 3D U-Net Cerebral Aneurysm Detection -- Detect and Identify Aneurysms Based on Ajusted 3D Attention Unet -- Cerebral Aneurysm Segmentation -- A$₩nu$-net: Automatic Detection and Segmentation of Aneurysm -- 3D Attention U-Net with pretraining: A Solution to CADA-Aneurysm Segmentation Challenge -- Exploring Large Context for Cerebral Aneurysm Segmentation -- Cerebral Aneurysm Rupture Risk Estimation -- CADA Challenge: Rupture risk assessment using Computational Fluid Dynamics -- Cerebral Aneurysm Rupture Risk Estimation Using XGBoost and Fully Connected Neural Network -- Intracranial aneurysm rupture risk estimation utilizing vessel-graphs and machine learning -- Intracranial aneurysm rupture prediction with computational fluid dynamics point clouds.▲ | |
520 | ▼aThis book constitutes the First Cerebral Aneurysm Detection Challenge, CADA 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in October 2020. The conference was planned to take place in Lima, Peru, and took place virtually due to the COVID-19 pandemic. The 9 regular papers presented in this volume, together with an overview and one introduction paper, were carefully reviewed and selected for inclusion in the book. The papers were organized in topical sections as follows: cerebral aneurysm detection; cerebral aneurysm segmentation; and cerebral aneurysm rupture risk estimation.▲ | ||
650 | 0 | ▼aImage processing—Digital techniques.▲ | |
650 | 0 | ▼aComputer vision.▲ | |
650 | 0 | ▼aApplication software.▲ | |
650 | 0 | ▼aMachine learning.▲ | |
650 | 0 | ▼aComputer science—Mathematics.▲ | |
650 | 1 | 4 | ▼aComputer Imaging, Vision, Pattern Recognition and Graphics.▲ |
650 | 2 | 4 | ▼aComputer and Information Systems Applications.▲ |
650 | 2 | 4 | ▼aMachine Learning.▲ |
650 | 2 | 4 | ▼aMathematics of Computing.▲ |
700 | 1 | ▼aHennemuth, Anja.▼eeditor.▼0(orcid)0000-0002-0737-7375▼1https://orcid.org/0000-0002-0737-7375▼4edt▼4http://id.loc.gov/vocabulary/relators/edt▲ | |
700 | 1 | ▼aGoubergrits, Leonid.▼eeditor.▼0(orcid)0000-0002-1961-3179▼1https://orcid.org/0000-0002-1961-3179▼4edt▼4http://id.loc.gov/vocabulary/relators/edt▲ | |
700 | 1 | ▼aIvantsits, Matthias.▼eeditor.▼4edt▼4http://id.loc.gov/vocabulary/relators/edt▲ | |
700 | 1 | ▼aKuhnigk, Jan-Martin.▼eeditor.▼4edt▼4http://id.loc.gov/vocabulary/relators/edt▲ | |
710 | 2 | ▼aSpringerLink (Online service)▲ | |
773 | 0 | ▼tSpringer Nature eBook▲ | |
776 | 0 | 8 | ▼iPrinted edition:▼z9783030728618▲ |
776 | 0 | 8 | ▼iPrinted edition:▼z9783030728632▲ |
830 | 0 | ▼aImage Processing, Computer Vision, Pattern Recognition, and Graphics ;▼v12643▲ | |
856 | 4 | 0 | ▼uhttps://doi.org/10.1007/978-3-030-72862-5▲ |
Cerebral Aneurysm Detection and Analysis[electronic resource] : First Challenge, CADA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings
자료유형
국외eBook
서명/책임사항
Cerebral Aneurysm Detection and Analysis [electronic resource] : First Challenge, CADA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings / edited by Anja Hennemuth, Leonid Goubergrits, Matthias Ivantsits, Jan-Martin Kuhnigk.
판사항
1st ed. 2021.
형태사항
X, 113 p. 47 illus., 41 illus. in color. online resource.
총서사항
내용주기
Overview of the CADA Challenge at MICCAI 2020 -- Cerebral Aneurysm Detection and Analysis Challenge 2020 (CADA) -- Introduction -- CADA: Clinical Background and Motivation -- Cerebral Aneurysm Detection -- Deep Learning-Based 3D U-Net Cerebral Aneurysm Detection -- Detect and Identify Aneurysms Based on Ajusted 3D Attention Unet -- Cerebral Aneurysm Segmentation -- A$\nu$-net: Automatic Detection and Segmentation of Aneurysm -- 3D Attention U-Net with pretraining: A Solution to CADA-Aneurysm Segmentation Challenge -- Exploring Large Context for Cerebral Aneurysm Segmentation -- Cerebral Aneurysm Rupture Risk Estimation -- CADA Challenge: Rupture risk assessment using Computational Fluid Dynamics -- Cerebral Aneurysm Rupture Risk Estimation Using XGBoost and Fully Connected Neural Network -- Intracranial aneurysm rupture risk estimation utilizing vessel-graphs and machine learning -- Intracranial aneurysm rupture prediction with computational fluid dynamics point clouds.
요약주기
This book constitutes the First Cerebral Aneurysm Detection Challenge, CADA 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in October 2020. The conference was planned to take place in Lima, Peru, and took place virtually due to the COVID-19 pandemic. The 9 regular papers presented in this volume, together with an overview and one introduction paper, were carefully reviewed and selected for inclusion in the book. The papers were organized in topical sections as follows: cerebral aneurysm detection; cerebral aneurysm segmentation; and cerebral aneurysm rupture risk estimation.
주제
ISBN
9783030728625
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