東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁 到查詢結果 [ subject:"Diagnostic imaging- Digital techniques" ]

切換: 標籤 | MARC模式 | ISBD

OR 2.0 context-aware operating theat...

OR 2.0 (Workshop) (2019 :)

FindBook

Google Book

Amazon

博客來

OR 2.0 context-aware operating theaters and machine learning in clinical Neuroimaging = second International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019 : proceedings /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	OR 2.0 context-aware operating theaters and machine learning in clinical Neuroimaging/ edited by Luping Zhou ... [et al.].
其他題名:	second International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019 : proceedings /
其他題名:	OR 2.0 2019
其他作者:	Zhou, Luping.
團體作者:	OR 2.0 (Workshop)
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	xvi, 114 p. :ill. (some col.), digital ;24 cm.
內容註:	Proceedings of the Second International Workshop on OR 2.0 Context-Aware Operating Theaters (OR 2.0 2019) -- Feature Aggregation Decoder for Segmenting Laparoscopic Scenes -- Preoperative Planning for Guidewires employing Shape-Regularized Segmentation and Optimized Trajectories -- Guided unsupervised desmoking of laparoscopic images using Cycle-Desmoke -- Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration -- Live monitoring of hemodynamic changes with multispectral image analysis -- Towards a Cyber-Physical Systems Based Operating Room of the Future -- Proceedings of the Second International Workshop on Machine Learning in Clinical Neuroimaging: Entering the era of big data via transfer learning and data harmonization (MLCN 2019) -- Deep Transfer Learning For Whole-Brain FMRI Analyses -- Knowledge distillation for semi-supervised domain adaptation -- Relevance Vector Machines for harmonization of MRI brain volumes using image descriptors -- Data Pooling and Sampling of Heterogeneous Image Data for White Matter Hyperintensity Segmentation -- A Hybrid 3DCNN and 3DC-LSTM based model for 4D Spatio-temporal fMRI data: An ABIDE Autism Classification study -- Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites.
Contained By:	Springer eBooks
標題:	Computer-assisted surgery - Congresses. -
電子資源:	https://doi.org/10.1007/978-3-030-32695-1
ISBN:	9783030326951

OR 2.0 context-aware operating theaters and machine learning in clinical Neuroimaging = second International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019 : proceedings /
OR 2.0 context-aware operating theaters and machine learning in clinical Neuroimagingsecond International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019 : proceedings /[electronic resource] :OR 2.0 2019edited by Luping Zhou ... [et al.]. - Cham :Springer International Publishing :2019. - xvi, 114 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,117960302-9743 ;. - Lecture notes in computer science ;11796..

Proceedings of the Second International Workshop on OR 2.0 Context-Aware Operating Theaters (OR 2.0 2019) -- Feature Aggregation Decoder for Segmenting Laparoscopic Scenes -- Preoperative Planning for Guidewires employing Shape-Regularized Segmentation and Optimized Trajectories -- Guided unsupervised desmoking of laparoscopic images using Cycle-Desmoke -- Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration -- Live monitoring of hemodynamic changes with multispectral image analysis -- Towards a Cyber-Physical Systems Based Operating Room of the Future -- Proceedings of the Second International Workshop on Machine Learning in Clinical Neuroimaging: Entering the era of big data via transfer learning and data harmonization (MLCN 2019) -- Deep Transfer Learning For Whole-Brain FMRI Analyses -- Knowledge distillation for semi-supervised domain adaptation -- Relevance Vector Machines for harmonization of MRI brain volumes using image descriptors -- Data Pooling and Sampling of Heterogeneous Image Data for White Matter Hyperintensity Segmentation -- A Hybrid 3DCNN and 3DC-LSTM based model for 4D Spatio-temporal fMRI data: An ABIDE Autism Classification study -- Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites.

This book constitutes the refereed proceedings of the Second International Workshop on Context-Aware Surgical Theaters, OR 2.0 2019, and the Second International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For OR 2.0 all 6 submissions were accepted for publication. They aim to highlight the potential use of machine vision and perception, robotics, surgical simulation and modeling, multi-modal data fusion and visualization, image analysis, advanced imaging, advanced display technologies, human-computer interfaces, sensors, wearable and implantable electronics and robots, visual attention models, cognitive models, decision support networks to enhance surgical procedural assistance, context-awareness and team communication in the operating theater, human-robot collaborative systems, and surgical training and assessment. MLCN 2019 accepted 6 papers out of 7 submissions for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience.

ISBN: 9783030326951

Standard No.: 10.1007/978-3-030-32695-1doiSubjects--Topical Terms:

1073759
Computer-assisted surgery
--Congresses.

LC Class. No.: RD29.7 / .O7 2019

Dewey Class. No.: 617.00285

OR 2.0 context-aware operating theaters and machine learning in clinical Neuroimaging = second International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019 : proceedings /
LDR:04113nmm a2200397 a 4500 001 2218847
003 DE-He213
005 20191027042018.0
006 m d
007 cr nn 008maaau
008 201126s2019 sz s 0 eng d
020 $a 9783030326951 $q (electronic bk.)
020 $a 9783030326944 $q (paper)
024 7 $a 10.1007/978-3-030-32695-1 $2 doi
035 $a 978-3-030-32695-1
040 $a GP $c GP
041 0 $a eng
050 4 $a RD29.7 $b .O7 2019
072 7 $a UYT $2 bicssc
072 7 $a COM012000 $2 bisacsh
072 7 $a UYT $2 thema
072 7 $a UYQV $2 thema
082 0 4 $a 617.00285 $2 23
090 $a RD29.7 $b .O63 2019
111 2 $a OR 2.0 (Workshop) $n (2nd : $d 2019 : $c Shenzhen Shi, China) $3 3453615
245 1 0 $a OR 2.0 context-aware operating theaters and machine learning in clinical Neuroimaging $h [electronic resource] : $b second International Workshop, OR 2.0 2019, and Second International Workshop, MLCN 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019 : proceedings / $c edited by Luping Zhou ... [et al.].
246 3 $a OR 2.0 2019
246 3 $a MLCN 2019
246 3 $a MICCAI 2019
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xvi, 114 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 11796
490 1 $a Image processing, computer vision, pattern recognition, and graphics
505 0 $a Proceedings of the Second International Workshop on OR 2.0 Context-Aware Operating Theaters (OR 2.0 2019) -- Feature Aggregation Decoder for Segmenting Laparoscopic Scenes -- Preoperative Planning for Guidewires employing Shape-Regularized Segmentation and Optimized Trajectories -- Guided unsupervised desmoking of laparoscopic images using Cycle-Desmoke -- Unsupervised Temporal Video Segmentation as an Auxiliary Task for Predicting the Remaining Surgery Duration -- Live monitoring of hemodynamic changes with multispectral image analysis -- Towards a Cyber-Physical Systems Based Operating Room of the Future -- Proceedings of the Second International Workshop on Machine Learning in Clinical Neuroimaging: Entering the era of big data via transfer learning and data harmonization (MLCN 2019) -- Deep Transfer Learning For Whole-Brain FMRI Analyses -- Knowledge distillation for semi-supervised domain adaptation -- Relevance Vector Machines for harmonization of MRI brain volumes using image descriptors -- Data Pooling and Sampling of Heterogeneous Image Data for White Matter Hyperintensity Segmentation -- A Hybrid 3DCNN and 3DC-LSTM based model for 4D Spatio-temporal fMRI data: An ABIDE Autism Classification study -- Automated Quantification of Enlarged Perivascular Spaces in Clinical Brain MRI across Sites.
520 $a This book constitutes the refereed proceedings of the Second International Workshop on Context-Aware Surgical Theaters, OR 2.0 2019, and the Second International Workshop on Machine Learning in Clinical Neuroimaging, MLCN 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. For OR 2.0 all 6 submissions were accepted for publication. They aim to highlight the potential use of machine vision and perception, robotics, surgical simulation and modeling, multi-modal data fusion and visualization, image analysis, advanced imaging, advanced display technologies, human-computer interfaces, sensors, wearable and implantable electronics and robots, visual attention models, cognitive models, decision support networks to enhance surgical procedural assistance, context-awareness and team communication in the operating theater, human-robot collaborative systems, and surgical training and assessment. MLCN 2019 accepted 6 papers out of 7 submissions for publication. They focus on addressing the problems of applying machine learning to large and multi-site clinical neuroimaging datasets. The workshop aimed to bring together experts in both machine learning and clinical neuroimaging to discuss and hopefully bridge the existing challenges of applied machine learning in clinical neuroscience.
650 0 $a Computer-assisted surgery $v Congresses. $3 1073759
650 0 $a Surgical robots $v Congresses. $3 3453617
650 0 $a Diagnostic imaging $x Digital techniques $v Congresses. $3 893046
650 1 4 $a Image Processing and Computer Vision. $3 891070
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Zhou, Luping. $3 2106824
710 2 $a SpringerLink (Online service) $3 836513
711 2 $a MLCN (Workshop) $n (2nd : $d 2019 : $c Shenzhen Shi, China) $3 3453618
711 2 $a International Conference on Medical Image Computing and Computer-Assisted Intervention $n (22nd : $d 2019 : $c Shenzhen Shi, China) $3 3446146
773 0 $t Springer eBooks
830 0 $a Lecture notes in computer science ; $v 11796. $3 3453616
830 0 $a Image processing, computer vision, pattern recognition, and graphics. $3 3382509
856 4 0 $u https://doi.org/10.1007/978-3-030-32695-1
950 $a Computer Science (Springer-11645)