07119nam 22007815 450 991035784700332120200902192021.03-030-33642-510.1007/978-3-030-33642-4(CKB)4100000009844989(DE-He213)978-3-030-33642-4(MiAaPQ)EBC5982923(PPN)257357815(EXLCZ)99410000000984498920191120d2019 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierLarge-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention[electronic resource] International Workshops, LABELS 2019, HAL-MICCAI 2019, and CuRIOUS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings /edited by Luping Zhou, Nicholas Heller, Yiyu Shi, Yiming Xiao, Raphael Sznitman, Veronika Cheplygina, Diana Mateus, Emanuele Trucco, X. Sharon Hu, Danny Chen, Matthieu Chabanas, Hassan Rivaz, Ingerid Reinertsen1st ed. 2019.Cham :Springer International Publishing :Imprint: Springer,2019.1 online resource (XX, 154 p. 62 illus., 48 illus. in color.) Image Processing, Computer Vision, Pattern Recognition, and Graphics ;118513-030-33641-7 Includes bibliographical references and index.4th 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.This 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.Image Processing, Computer Vision, Pattern Recognition, and Graphics ;11851Optical data processingArtificial intelligenceHealth informaticsImage Processing and Computer Visionhttps://scigraph.springernature.com/ontologies/product-market-codes/I22021Artificial Intelligencehttps://scigraph.springernature.com/ontologies/product-market-codes/I21000Health Informaticshttps://scigraph.springernature.com/ontologies/product-market-codes/I23060Optical data processing.Artificial intelligence.Health informatics.Image Processing and Computer Vision.Artificial Intelligence.Health Informatics.006.6006.37Zhou Lupingedthttp://id.loc.gov/vocabulary/relators/edtHeller Nicholasedthttp://id.loc.gov/vocabulary/relators/edtShi Yiyuedthttp://id.loc.gov/vocabulary/relators/edtXiao Yimingedthttp://id.loc.gov/vocabulary/relators/edtSznitman Raphaeledthttp://id.loc.gov/vocabulary/relators/edtCheplygina Veronikaedthttp://id.loc.gov/vocabulary/relators/edtMateus Dianaedthttp://id.loc.gov/vocabulary/relators/edtTrucco Emanueleedthttp://id.loc.gov/vocabulary/relators/edtHu X. Sharonedthttp://id.loc.gov/vocabulary/relators/edtChen Dannyedthttp://id.loc.gov/vocabulary/relators/edtChabanas Matthieuedthttp://id.loc.gov/vocabulary/relators/edtRivaz Hassanedthttp://id.loc.gov/vocabulary/relators/edtReinertsen Ingeridedthttp://id.loc.gov/vocabulary/relators/edtInternational Workshop, LABELS(2019),International Workshop, HAL-MICCAI(2019),International Workshop, CuRIOUS(2019),International Workshop, MICCAI(2019 :Shenzhen, China),MiAaPQMiAaPQMiAaPQBOOK9910357847003321Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention2501924UNINA