WorkstationJ as ImageJ Plugin for Medical Image Studies

Transcription

1 WorkstationJ as ImageJ Plugin for Medical Image Studies Kevin M. Schartz, PhD, MCS; Kevin S. Berbaum, PhD; Robert T. Caldwell, MFA; Mark T. Madsen, PhD Department of Radiology, The University of Iowa, Iowa City, IA WorkstationJ plugin conversion funded by a 2008 Product Support Grant from The Society for Imaging Informatics in Medicine Original WorkstationJ development funded by a supplement to NIH Grant R01-EB000145

2 Outline Motivation for original WorkstationJ development Characteristics & functionality of WorkstationJ Converting the stand-alone WorkstationJ program to be a plugin to ImageJ

3 The Problem Many medical image perception studies are conducted by individual investigators at a single institution rather than collaborations among investigators at multiple institutions. The number of expert readers at a particular institution is limited, so collaboration is necessary.

4 Pool Resources to Increase Statistical Power Investigators could share cases to build a larger case pool. So, statistical power could be improved by having readers at multiple institutions read the pool of cases.

5 Software Impediments Conducting medical image perception and technology evaluation studies with multiple institutions can be hindered by the need to use commercial image presentation software. Using a common software platform capable of collecting observer responses and real-time interactions with the display would facilitate the collection and pooling of data from multiple institutions.

6 Our Solution Develop our own software for conducting image perception and technology evaluation studies Develop software that does not rely on commercial or proprietary software components

7 WorkstationJ Mimics the functionality available in commercial clinical systems Records time-stamped, observerdisplay interactions, including inspection time, window/level, and magnification

8 WorkstationJ Overview Plugins are developed to provide image layout configurations and to provide study navigation controls. Researchers write simple text-based script files that are read by these plugins to conduct their studies.

9 Script Files Provide the names of the image files Control aspects of the image display such as initial window/level setting Tag/classify cases (e.g., normal/abnormal) Specify how to randomize presentation of cases

10 Sample Script RND$ fixed=2; blocks=2, prompt=1 SET$ wlpreset=mdst COM$ DEMO TTL$ C:\Chest Cases\titles\69F.tif TTL$ C:\Chest Cases\titles\fatty liver.tif NOT$ TTL$ C:\Chest Cases\titles\demo.tif VOX$ C:\Chest Cases\cases\A411.vox $ COM$ PRACTICE TTL$ C:\Chest Cases\titles\38F.tif NOT$ NOT$ TTL$ C:\Chest Cases\titles\practice.tif VOX$ C:\Chest Cases\cases\CT 215.vox $

11 CT Display

12 CT Display w/ Response Dialog

13 Log File User-display interactions such as: inspection time image window/level image magnification slice navigation

14 Log is Event-driven Interacting with display triggers an event. A time-stamped, structured, textual description of the event is written to the log file. Each log entry is tagged to indicate the type of event that generated it.

15 Summaries of Observer Behavior Image exploration as a function of elapsed time Cumulative viewing time for each slice

16 Software Requirements WorkstationJ is packaged as a Java jar file and Java class files that are added to an ImageJ installation. WorkstationJ does not rely on any commercial or proprietary software components or any specific hardware.

17 Supported Image Modalities Currently capable of displaying CT and computed radiography images For CTs, performance is greatly improved if the DICOM sequence is first converted to a single voxel file. Could be adapted for displaying images from other modalities such as MR

18 WorkstationJ WorkstationJ makes it possible to increase reader sample sizes by collecting data at multiple locations without purchasing commercial systems for each location. Each location needs only a computer, a monitor or panel capable of displaying the needed resolution and image quality, and the software.

19 History WorkstationJ was originally developed in 2003 as a stand-alone program by extensively modifying the ImageJ classes. Many WorkstationJ-specific classes were also created over the years.

20 Advantages of Plugin Version Improvements/bug fixes in ImageJ are readily available to WorkstationJ users Can leave core functionality to ImageJ and focus on researchspecific coding

21 Disadvantages of Plugin Version Changes in ImageJ could break WorkstationJ (e.g., return types of methods could change) Some functionality in ImageJ could be undesirable in WorkstationJ (e.g., keystrokes could launch filters or other transformations to the image)

22 Converting from Stand-alone to Plugin Version It was first necessary to identify which ImageJ classes had been modified. These classes had to be subclassed or replaced.

23 Conversion to Plugin, cont. WorkstationJ was revised so that only five ImageJ classes had to be extended in the ij and ij.gui packages. These were ImagePlus, ImageWindow, StackWindow, ImageCanvas, and GUI classes.

24 Conversion to plugin, cont. After creating the extended classes, the existing WorkstationJ classes and plugins were rewritten to use these extended classes. There are numerous WorkstationJspecific classes that implement the script parsing, experiment layout and control, data collection, and logging functionality.

25 Installation Overview Requires Java SE 5 (or later) JDK ImageJ 1.41 must first be installed (a Windows installer is available) A jar file and the class files for the plugins must be copied to appropriate folders of the ImageJ installation Modify classpath argument to use the new jar file

26 Additional Information & Downloads The University of Iowa Medical Image Perception Website: ImageJ website:

27

28 Multi-modality Display

29 CT Maximized

30 Radiograph Maximized

31 Classes vs. Objects In OOP, classes are blueprints or specifications for how objects are constructed. They define the data and the methods that will operate on the data. In OOP, objects are instantiations of classes that exist at runtime.

32 Inheritance Example In WorkstationJ, there is a WorkstationImageCanvas class that extends the ImageCanvas class from ImageJ. Most of the data and methods in the ImageCanvas class are inherited by the WorkstationImageCanvas class.

33 Polymorphism Because of the is-a relationship between a subclass and a superclass, it is possible for subclasses to be used where a superclass was expected. Example: WorkstationImageCanvas objects would be accepted by methods expecting an ImageCanvas object.