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000917452 020__ $$a9783030336424$$q(electronic book)
000917452 020__ $$a3030336425$$q(electronic book)
000917452 020__ $$z9783030336417
000917452 0248_ $$a10.1007/978-3-030-33
000917452 035__ $$aSP(OCoLC)on1129167314
000917452 035__ $$aSP(OCoLC)1129167314
000917452 040__ $$aLQU$$beng$$cLQU$$dGW5XE$$dOCLCO
000917452 049__ $$aISEA
000917452 050_4 $$aR858.A2
000917452 08204 $$a006.37
000917452 08204 $$a006.6
000917452 1112_ $$aLABELS (Workshop)$$n(4th :$$d2019 :$$cShenzhen Shi, China)
000917452 24510 $$aLarge-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention :$$bInternational Workshops, LABELS 2019, HAL-MICCAI 2019, and CuRIOUS 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings /$$cLuping Zhou, Nicholas Heller, Yiyu Shi, Yiming Xiao et al. (eds.).
000917452 264_1 $$aCham :$$bSpringer,$$c2019.
000917452 300__ $$a1 online resource (xx, 154 pages) :$$billustrations.
000917452 336__ $$atext$$btxt$$2rdacontent
000917452 337__ $$acomputer$$bc$$2rdamedia
000917452 338__ $$aonline resource$$bcr$$2rdacarrier
000917452 4901_ $$aLecture notes in computer science ;$$v11851
000917452 4901_ $$aLNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics
000917452 500__ $$aInternational conference proceedings.
000917452 5050_ $$a4th International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis (LABELS 2019) -- Comparison of active learning strategies applied to lung nodule segmentation in CT scans -- Robust Registration of Statistical Shape Models for Unsupervised Pathology Annotation -- XiangyaDerm: A Clinical Image Dataset of Asian Race for Skin Disease Aided Diagnosis -- Data Augmentation based on Substituting Regional MRI Volume Scores -- Weakly supervised segmentation from extreme points -- Exploring the Relationship between Segmentation Uncertainty, Segmentation Performance and Inter-observer Variability with Probabilistic Networks -- DeepIGeoS-V2: Deep Interactive Segmentation of Multiple Organs from Head and Neck Images with Lightweight CNNs -- The Role of Publicly Available Data in MICCAI Papers from 2014 to 2018 -- First International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention (HAL-MICCAI 2019) -- Hardware Acceleration of Persistent Homology Computation -- Deep Compressed Pneumonia Detection for Low-Power Embedded Devices -- D3MC: A Reinforcement Learning based Data-driven Dyna Model Compression -- An Analytical Method of Automatic Alignment for Electron Tomography -- Fixed-Point U-Net Quantization for Medical Image Segmentation -- Second International Workshop on Correction of Brainshift with Intra-Operative Ultrasound (CuRIOUS 2019) -- Registration of ultrasound volumes based on Euclidean distance transform -- Landmark-based evaluation of a block-matching registration framework on the RESECT pre- and intra-operative brain image data set -- Comparing deep learning strategies and attention mechanisms of discrete registration for multimodal image-guided interventions.
000917452 506__ $$aAccess limited to authorized users.
000917452 520__ $$aThis book constitutes the refereed joint proceedings of the 4th International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2019, the First International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention, HAL-MICCAI 2019, and the Second International Workshop on Correction of Brainshift with Intra-Operative Ultrasound, CuRIOUS 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 8 papers presented at LABELS 2019, the 5 papers presented at HAL-MICCAI 2019, and the 3 papers presented at CuRIOUS 2019 were carefully reviewed and selected from numerous submissions. The LABELS papers present a variety of approaches for dealing with a limited number of labels, from semi-supervised learning to crowdsourcing. The HAL-MICCAI papers cover a wide set of hardware applications in medical problems, including medical image segmentation, electron tomography, pneumonia detection, etc. The CuRIOUS papers provide a snapshot of the current progress in the field through extended discussions and provide researchers an opportunity to characterize their image registration methods on newly released standardized datasets of iUS-guided brain tumor resection.
000917452 650_0 $$aMedical informatics$$vCongresses.
000917452 650_0 $$aBiomedical engineering$$vCongresses.
000917452 650_0 $$aRadiography, Medical$$vCongresses.
000917452 7001_ $$aZhou, Luping.
000917452 7001_ $$aHeller, Nicholas.
000917452 7001_ $$aShi, Yiyu.
000917452 7001_ $$aXiao, Yiming.
000917452 7112_ $$aHAL-MICCAI (Workshop)$$n(1st :$$d2019 :$$cShenzhen Shi, China),$$jjointly held conference.
000917452 7112_ $$aCuRIOUS (Workshop)$$n(2nd :$$d2019 :$$cShenzhen Shi, China),$$jjointly held conference.
000917452 7112_ $$aInternational Conference on Medical Image Computing and Computer-Assisted Intervention$$n(22nd :$$d2019 :$$cShenzhen Shi, China),$$jjointly held conference.
000917452 830_0 $$aLecture notes in computer science ;$$v11851.
000917452 830_0 $$aLNCS sublibrary.$$nSL 6,$$pImage processing, computer vision, pattern recognition, and graphics.
000917452 852__ $$bebk
000917452 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-33642-4$$zOnline Access$$91397441.1
000917452 909CO $$ooai:library.usi.edu:917452$$pGLOBAL_SET
000917452 980__ $$aEBOOK
000917452 980__ $$aBIB
000917452 982__ $$aEbook
000917452 983__ $$aOnline
000917452 994__ $$a92$$bISE