3D U-Net Based Semantic Segmentation of Kidneys and Renal Masses on Contrast-Enhanced CT (Englisch)
- Neue Suche nach: Zang, Mingyang
- Neue Suche nach: Wysoczanski, Artur
- Neue Suche nach: Angelini, Elsa
- Neue Suche nach: Laine, Andrew F.
- Neue Suche nach: Heller, Nicholas
- Weitere Informationen zu Heller, Nicholas:
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https://orcid.org/https://orcid.org/0000-0001-8516-8707
- Neue Suche nach: Isensee, Fabian
- Weitere Informationen zu Isensee, Fabian:
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https://orcid.org/https://orcid.org/0000-0002-3519-5886
- Neue Suche nach: Trofimova, Darya
- Neue Suche nach: Tejpaul, Resha
- Neue Suche nach: Papanikolopoulos, Nikolaos
- Weitere Informationen zu Papanikolopoulos, Nikolaos:
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https://orcid.org/https://orcid.org/0000-0002-2177-1870
- Neue Suche nach: Weight, Christopher
- Neue Suche nach: Zang, Mingyang
- Neue Suche nach: Wysoczanski, Artur
- Neue Suche nach: Angelini, Elsa
- Neue Suche nach: Laine, Andrew F.
In:
Kidney and Kidney Tumor Segmentation
: MICCAI 2021 Challenge, KiTS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings
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Kapitel: 19
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143-150
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2022
- Aufsatz/Kapitel (Buch) / Elektronische Ressource
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Titel:3D U-Net Based Semantic Segmentation of Kidneys and Renal Masses on Contrast-Enhanced CT
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Weitere Titelangaben:Lect.Notes Computer
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Beteiligte:Heller, Nicholas ( Herausgeber:in ) / Isensee, Fabian ( Herausgeber:in ) / Trofimova, Darya ( Herausgeber:in ) / Tejpaul, Resha ( Herausgeber:in ) / Papanikolopoulos, Nikolaos ( Herausgeber:in ) / Weight, Christopher ( Herausgeber:in ) / Zang, Mingyang ( Autor:in ) / Wysoczanski, Artur ( Autor:in ) / Angelini, Elsa ( Autor:in ) / Laine, Andrew F. ( Autor:in )
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Kongress:International Challenge on Kidney and Kidney Tumor Segmentation ; 2021 ; Strasbourg, France
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Erschienen in:Kidney and Kidney Tumor Segmentation : MICCAI 2021 Challenge, KiTS 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings ; Kapitel: 19 ; 143-150Lecture Notes in Computer Science ; 13168 ; 143-150
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Verlag:
- Neue Suche nach: Springer International Publishing
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Erscheinungsort:Cham
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Erscheinungsdatum:25.03.2022
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Format / Umfang:8 pages
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ISBN:
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ISSN:
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DOI:
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Medientyp:Aufsatz/Kapitel (Buch)
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Format:Elektronische Ressource
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Sprache:Englisch
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Schlagwörter:
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Datenquelle:
Inhaltsverzeichnis E-Book
Die Inhaltsverzeichnisse werden automatisch erzeugt und basieren auf den im Index des TIB-Portals verfügbaren Einzelnachweisen der enthaltenen Beiträge. Die Anzeige der Inhaltsverzeichnisse kann daher unvollständig oder lückenhaft sein.
- 1
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Automated Kidney Tumor Segmentation with Convolution and Transformer NetworkShen, Zhiqiang / Yang, Hua / Zhang, Zhen / Zheng, Shaohua et al. | 2022
- 2
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Extraction of Kidney Anatomy Based on a 3D U-ResNet with Overlap-Tile StrategyAdam, Jannes / Agethen, Niklas / Bohnsack, Robert / Finzel, René / Günnemann, Timo / Philipp, Lena / Plutat, Marcel / Rink, Markus / Xue, Tingting / Thielke, Felix et al. | 2022
- 3
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Modified nnU-Net for the MICCAI KiTS21 ChallengeXu, Lizhan / Shi, Jiacheng / Dong, Zhangfu et al. | 2022
- 4
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2.5D Cascaded Semantic Segmentation for Kidney Tumor CystChen, Zhiwei / Liu, Hanqiang et al. | 2022
- 5
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Automated Machine Learning Algorithm for Kidney, Kidney Tumor, Kidney Cyst Segmentation in Computed Tomography ScansPawar, Vivek / Kss, Bharadwaj et al. | 2022
- 6
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Three Uses of One Neural Network: Automatic Segmentation of Kidney Tumor and Cysts Based on 3D U-NetLv, Yi / Wang, Junchen et al. | 2022
- 7
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Less is More: Contrast Attention Assisted U-Net for Kidney, Tumor and Cyst SegmentationsWu, Mengran / Liu, Zhiyang et al. | 2022
- 8
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A Coarse-to-Fine Framework for the 2021 Kidney and Kidney Tumor Segmentation ChallengeZhao, Zhongchen / Chen, Huai / Wang, Lisheng et al. | 2022
- 9
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Kidney and Kidney Tumor Segmentation Using a Two-Stage Cascade FrameworkLin, Chaonan / Fu, Rongda / Zheng, Shaohua et al. | 2022
- 10
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Squeeze-and-Excitation Encoder-Decoder Network for Kidney and Kidney Tumor Segmentation in CT ImagesWen, Jianhui / Li, Zhaopei / Shen, Zhiqiang / Zheng, Yaoyong / Zheng, Shaohua et al. | 2022
- 11
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A Two-Stage Cascaded Deep Neural Network with Multi-decoding Paths for Kidney Tumor SegmentationHe, Tian / Zhang, Zhen / Pei, Chenhao / Huang, Liqin et al. | 2022
- 12
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Mixup Augmentation for Kidney and Kidney Tumor SegmentationGazda, Matej / Bugata, Peter / Gazda, Jakub / Hubacek, David / Hresko, David Jozef / Drotar, Peter et al. | 2022
- 13
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Automatic Segmentation in Abdominal CT Imaging for the KiTS21 ChallengeHeo, Jimin et al. | 2022
- 14
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An Ensemble of 3D U-Net Based Models for Segmentation of Kidney and Masses in CT ScansGolts, Alex / Khapun, Daniel / Shats, Daniel / Shoshan, Yoel / Gilboa-Solomon, Flora et al. | 2022
- 15
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Contrast-Enhanced CT Renal Tumor SegmentationXiao, Chuda / Hassan, Haseeb / Huang, Bingding et al. | 2022
- 16
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A Cascaded 3D Segmentation Model for Renal Enhanced CT ImagesLi, Dan / Chen, Zhuo / Hassan, Haseeb / Xie, Weiguo / Huang, Bingding et al. | 2022
- 17
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Leveraging Clinical Characteristics for Improved Deep Learning-Based Kidney Tumor Segmentation on CTLund, Christina B. / van der Velden, Bas H. M. et al. | 2022
- 18
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A Coarse-to-Fine 3D U-Net Network for Semantic Segmentation of Kidney CT ScansGeorge, Yasmeen et al. | 2022
- 19
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3D U-Net Based Semantic Segmentation of Kidneys and Renal Masses on Contrast-Enhanced CTZang, Mingyang / Wysoczanski, Artur / Angelini, Elsa / Laine, Andrew F. et al. | 2022
- 20
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Kidney and Kidney Tumor Segmentation Using Spatial and Channel Attention Enhanced U-NetGohil, Sajan / Lad, Abhi et al. | 2022
- 21
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Transfer Learning for KiTS21 ChallengeYang, Xi / Zhang, Jianpeng / Zhang, Jing / Xia, Yong et al. | 2022