OR 2.0 Context-Aware Operating Theaters and Machine Learning in Clinical Neuroimaging [electronic resource] : 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 / edited by Luping Zhou, Duygu Sarikaya, Seyed Mostafa Kia, Stefanie Speidel, Anand Malpani, Daniel Hashimoto, Mohamad Habes, Tommy Löfstedt, Kerstin Ritter, Hongzhi Wang.
Contributor(s): Zhou, Luping [editor.] | Sarikaya, Duygu [editor.] | Kia, Seyed Mostafa [editor.] | Speidel, Stefanie [editor.] | Malpani, Anand [editor.] | Hashimoto, Daniel [editor.] | Habes, Mohamad [editor.] | Löfstedt, Tommy [editor.] | Ritter, Kerstin [editor.] | Wang, Hongzhi [editor.] | SpringerLink (Online service).
Material type: BookSeries: Image Processing, Computer Vision, Pattern Recognition, and Graphics: 11796Publisher: Cham : Springer International Publishing : Imprint: Springer, 2019Edition: 1st ed. 2019.Description: XVI, 114 p. 35 illus., 33 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030326951.Subject(s): Computer vision | Artificial intelligence | Computer Vision | Artificial IntelligenceAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.37 Online resources: Click here to access onlineProceedings 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.
Chapter 5 is available open access under a Creative Commons Attribution 4.0 International License via Springerlink.
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