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 / 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 Reinertsen.

Format:

Book

Contributor:

Zhou, Luping, Editor.

Heller, Nicholas, Editor.

Shi, Yiyu., Editor.

Xiao, Yiming, Editor.

Sznitman, Raphael, Editor.

Cheplygina, Veronika., Editor.

Mateus, Diana., Editor.

Trucco, Emanuele, Editor.

Hu, X. Sharon., Editor.

Chen, Danny., Editor.

Chabanas, Matthieu., Editor.

Rivaz, Hassan., Editor.

Reinertsen, Ingerid., Editor.

SpringerLink (Online service)

Series:

Computer Science (SpringerNature-11645)

LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics ; SL 6, 11851

Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11851

Language:

English

Subjects (All):

Computer vision.

Artificial intelligence.

Medical informatics.

Computer Vision.

Artificial Intelligence.

Health Informatics.

Local Subjects:

Computer Vision.

Artificial Intelligence.

Health Informatics.

Physical Description:

1 online resource (XX, 154 pages) : 62 illustrations, 48 illustrations in color.

Edition:

1st ed. 2019.

Contained In:

Springer Nature eBook

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2019.

System Details:

text file PDF

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, et cetera 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.

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 Format:

Printed edition:

ISBN:

978-3-030-33642-4

9783030336424

Access Restriction:

Restricted for use by site license.