Cloud-Based Benchmarking of Medical Image Analysis / edited by Allan Hanbury, Henning Müller, Georg Langs.

Format:

Book

Author/Creator:

Georg Langs

Contributor:

Hanbury, Allan, Editor.

Müller, Henning, Editor.

Langs, Georg, Editor.

Series:

Computer Science Series

Language:

English

Subjects (All):

Medical informatics.

Optical data processing.

Computer system failures.

Health Informatics.

Image Processing and Computer Vision.

System Performance and Evaluation.

Local Subjects:

Health Informatics.

Image Processing and Computer Vision.

System Performance and Evaluation.

Physical Description:

1 online resource (XVIII, 254 p. 93 illus., 39 illus. in color.)

Edition:

1st ed. 2017.

Place of Publication:

Springer Nature 2017

Cham : Springer International Publishing : Imprint: Springer, 2017.

Language Note:

English

Summary:

This book is open access under a CC BY-NC 2.5 license. This book presents the VISCERAL project benchmarks for analysis and retrieval of 3D medical images (CT and MRI) on a large scale, which used an innovative cloud-based evaluation approach where the image data were stored centrally on a cloud infrastructure and participants placed their programs in virtual machines on the cloud. The book presents the points of view of both the organizers of the VISCERAL benchmarks and the participants. The book is divided into five parts. Part I presents the cloud-based benchmarking and Evaluation-as-a-Service paradigm that the VISCERAL benchmarks used. Part II focuses on the datasets of medical images annotated with ground truth created in VISCERAL that continue to be available for research. It also covers the practical aspects of obtaining permission to use medical data and manually annotating 3D medical images efficiently and effectively. The VISCERAL benchmarks are described in Part III, including a presentation and analysis of metrics used in evaluation of medical image analysis and search. Lastly, Parts IV and V present reports by some of the participants in the VISCERAL benchmarks, with Part IV devoted to the anatomy benchmarks and Part V to the retrieval benchmark. This book has two main audiences: the datasets as well as the segmentation and retrieval results are of most interest to medical imaging researchers, while eScience and computational science experts benefit from the insights into using the Evaluation-as-a-Service paradigm for evaluation and benchmarking on huge amounts of data.

Contents:

VISCERAL: Evaluation-as-a-Service for Medical Imaging

Using the Cloud as a Platform for Evaluation and Data Preparation

Ethical and Privacy Aspects of Using Medical Image Data

Annotating Medical Image Data

Datasets created in VISCERAL

Evaluation Metrics for Medical Organ Segmentation and Lesion Detection

VISCERAL Anatomy Benchmarks for Organ Segmentation and Landmark Localisation: Tasks and Results

Retrieval of Medical Cases for Diagnostic Decisions: VISCERAL Retrieval Benchmark

Automatic Atlas-Free Multi-Organ Segmentation of Contrast-Enhanced CT Scans

Multi-organ Segmentation Using Coherent Propagating Level Set Method Guided by Hierarchical Shape Priors and Local Phase Information

Automatic Multi-organ Segmentation using Hierarchically-Registered Probabilistic Atlases

Multi-Atlas Segmentation Using Robust Feature-Based Registration

Combining Radiology Images and Clinical Meta-data for Multimodal Medical Case-based Retrieval

Text and Content-based Medical Image Retrieval in the VISCERAL Retrieval Benchmark.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

3-319-49644-1

OCLC:

1073090964