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Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention : International Workshops, LABELS 2019, HAL-MICCAI 2019, and CuRIOUS 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings. LABELS (Workshop) (4th : 2019 : Shenzhen Shi, China)
- Author(s):
- Zhou, Luping
- Heller, Nicholas
- Shi, Yiyu
- Xiao, Yiming
- LABELS (Workshop) (4th 2019 Shenzhen Shi China)
- HAL-MICCAI (Workshop) (1st 2019 Shenzhen Shi China), jointly held conference
- CuRIOUS (Workshop) (2nd 2019 Shenzhen Shi China), jointly held conference
- International Conference on Medical Image Computing and Computer-Assisted Intervention (22nd 2019 Shenzhen Shi China), jointly held conference
- NLM Title Abbreviation:
- Large Scale Annot Biomed Data Export Label Synth Hardw Aware Learn Med Imaging Comput Assist Interv (2019)
- Title(s):
- Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention : International Workshops, LABELS 2019, HAL-MICCAI 2019, and CuRIOUS 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings / Luping Zhou, Nicholas Heller, Yiyu Shi, Yiming Xiao et al. (eds.).
- Series:
- Lecture notes in computer science ; 11851
LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics
- Country of Publication:
- Switzerland
- Publisher:
- Cham : Springer, 2019.
- Description:
- 1 online resource (xx, 154 pages) : illustrations (some color)
-
Language:
- English
- ISBN:
- 9783030336424
3030336425
9783030336417
- Electronic Links:
- Access not provided by NLM
- Summary:
- 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.
- In:
- PubMed: Selected citations only
- Current Indexing Status:
- Not currently indexed for MEDLINE. Citations are for articles where the manuscript was deposited in PubMed Central (PMC) in compliance with public access policies. For further information, see Author Manuscripts in PMC.
- Notes:
- International conference proceedings.
Includes bibliographical references and author index.
Also issued in print.
- Contents:
- 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.
- Other ID:
- (OCoLC)1129167314
- Collection Status:
- Not in the NLM Collection
- NLM ID:
- 101771011 [Electronic Resource]