Insight Journal (ISSN 2327-770X) - Next Generation of the JAVA Image Science Toolkit (JIST) Visualization and Validation

Next Generation of the JAVA Image Science Toolkit (JIST) Visualization and Validation

Please use this identifier to cite or link to this publication: http://hdl.handle.net/10380/3378

Published in The Insight Journal - 2012 January-December.

Submitted by Bo Li on 08-14-2012.

Modern medical imaging analyses often involve the concatenation of multiple steps, and neuroimaging analysis is no exception. The Java Image Science Toolkit (JIST) has provided a framework for both end users and engineers to synthesize processing modules into tailored, automatic multi-step processing pipelines (“layouts”) and rapid prototyping of module development. Since its release, JIST has facilitated substantial neuroimaging research and fulfilled much of its intended goal. However, key weaknesses must be addressed for JIST to more fully realize its potential and become accessible to an even broader community base. Herein, we identify three core challenges facing traditional JIST (JIST-I) and present the solutions in the next generation JIST (JIST-II). First, in response to community demand, we have introduced seamless data visualization; users can now click ‘show this data’ through the program interfaces and avoid the need to locating files on the disk. Second, as JIST is an open-source community effort by-design; any developer may add modules to the distribution and extend existing functionality for release. However, the large number of developers and different use cases introduced instability into the overall JIST-I framework, causing users to freeze on different, incompatible versions of JIST-I, and the JIST community began to fracture. JIST-II addresses the problem of compilation instability by performing continuous integration checks nightly to ensure community implemented changes do not negatively impact overall JIST-II functionality. Third, JIST-II allows developers and users to ensure that functionality is preserved by running functionality checks nightly using the continuous integration framework. With JIST-II, users can submit layout test cases and quality control criteria through a new GUI. These test cases capture all runtime parameters and help to ensure that the module produces results within tolerance, despite changes in the underlying architecture. These three “next generation” improvements increase the fidelity of the JIST framework and enhance utility by allowing researchers to more seamlessly and robustly build, manage, and understand medical image analysis processing pipelines.

Code

There is no code review at this time.

Reviews

Next Generation of the JAVA Image Science Toolkit(JIST) Visualization and Validation by Jung-san Lee on 2013-01-22 21:57:49 for revision #1

expertise: 4 sensitivity: 5

Summary:

This paper proposes the next generation for Java Image Science Toolkit (JIST), which realize the visualization function and validation for the integrated medical image processing platform to ease the whole medical image process, and analytically prevents the inaccuracy from degrading the performance of open-source development.

Hypothesis:

Finite medical imaging processing algorithms components.

Evidence:

Different medical imaging processing pipelines are formed to process different medical image data and realize several complex algorithems cross platforms.

Open Science:

Yes.

Reproducibility:

Yes.

The source code compiles and runs well.

Use of Open Source Software:

The authors not only describe the open source advantages, but also provide the open source nightly build validation workflow with Hudson.

Open source Contributions:

Yes.

The code is clear and easy to run.

Code Quality :

The code is well written and suitable for multiple-platforms.

Quality of the data :

The data provided is usable and make sense.

Interest:

More imaging processing algorithms could be developped within this tool.

Free comment :

The platform is flexible on different operating systems, and the pipeline is reusable and designable for researchers to implement their own algorithms with specific data as well as handling various data analyses. The paper is well organized with strong theoretical results and comprehensive evaluation studies with real traces collected from multiple complex medical image processing algorithms and neuroimage data.

It is also desired that the authors provide some discussions of the open-source challenges and opportunities and offer the solutions with Hudson to realize the nightly build validation analysis.

The Code attached works well and the open-source platform works efficiently with helps of Hudson nightly build procedures, which provide a nice developing environment for the developers for JIST.

Overall, the paper is well organized with strong theoretical results and comprehensive evaluation studies on the clinic neuroimage dataset.

Comment by Itezziodiss Holland:

Comment by Pshopgolf Olivier:

Comment by Umcglaufllind Olivier:

Comment by Nhuskinsaran Ken:

Comment by Aollwaymyrt Vigorda:

Comment by Rankeurensuan Ken:

Comment by Ekjamerkend Ken:

Comment by Pshopgolf Olivier:

Comment by Aollwaymyrt Vigorda:

Comment by Rnseremmi Vigorda:

Comment by Defeldanni Vigorda:

Comment by Aollwaymyrt Vigorda:

Comment by Pshopgolf Olivier:

Comment by Bridesmaidbride Ken:

Comment by Mwangmajor Holland:

Comment by Defeldanni Vigorda:

Comment by Bridesmaidbride Ken:

Comment by Eveningdiscount Ken:

Comment by Itezziodiss Holland:

Comment by Uejesusrodg Holland:

Comment by Pshopgolf Olivier:

Comment by Itezziodiss Holland:

Comment by Mwangmajor Holland:

Comment by :

Comment by Mwangmajor Holland:

Comment by Lheeralalkris Olivier:

Comment by Tyamatriley Vigorda:

Comment by :

Comment by Elogoleorodr Olivier:

Comment by Aollwaymyrt Vigorda:

Comment by Uejesusrodg Holland:

Comment by Itezziodiss Holland:

Comment by Pshopgolf Olivier:

Comment by :

Comment by Defeldanni Vigorda:

Comment by :

Comment by Defeldanni Vigorda:

Comment by :

Comment by Ndiscountcanada Olivier:

Comment by :

Comment by Tsmccathedema Ken:

Comment by :

Comment by Tsmccathedema Ken:

Comment by Lheeralalkris Olivier:

Add a new review

Quick Comments

Resources


Download All
Download Paper , View Paper
Download Source code

Statistics more


Global rating:
Review rating:	[review]
Code rating:
Views:	23166
Downloads:	4134
Paper Quality:

Information more


Paper Id:	874
Categories:	Data Representation, Programming
Keywords:	JIST next generation, medical image analysis, visualization, fidelity, continuous integration
Revision:
Export citation:
Status:	Open for public review

Share

Linked Publications more


A Skull-Stripping Filter for ITK by Bauer S., Fejes T., Reyes M.
Importing Contours from DICOM-RT Structure Sets by Dowling J., Malaterre M., Greer P.B., Salvado O.
Laplace Beltrami Filter on QuadEdge Meshes by Bowers M., Younes L.
Diffeomorphic Demons Using ITK's Finite Difference Solver Hierarchy by Vercauteren T., Pennec X., Perchant A., Ayache N.
MUSiiC ToolKit 2.0: Bidirectional Real-time Software Framework for Advanced Interventional... by Kang H., Cheng A., Boctor E.
A Label Geometry Image Filter for Multiple Object Measurement by Padfield D., Miller J.
Structural MRI Unwarping Using CMTK by Rohlfing T.
Anisotropic Fast Marching in ITK by Mirebeau J.
ITK in Biomedical Research and Commercial Applications by McCormick M., Aylward S., Johnson H., Lowekamp B.
An ITK Implementation of Physics-based Non-rigid Registration Method by Liu Y., Kot A., Drakopoulos F., Fedorov A., Enquobahrie A., Clatz O., Chrisochoides N.

View license

Loading license...

Send a message to the author