Excel2Genie, a simple and user friendly Microsoft Excel interface has been developed to the Genie-2000 Spectroscopic Software of Canberra Industries. This Excel application can directly control Canberra Multichannel Analyzer (MCA), process the acquired data and visualize them. Combination of Genie-2000 with Excel2Genie results in remarkably increased flexibility and in a possibility to carry out repetitive data acquisitions even with changing parameters and more sophisticated analysis. The developed software package is comprised of three worksheet; display parameters and results of data acquisition, data analysis and mathematical operations carried out on the measured gamma spectra. At the same time it also allows control of these processes.

Before using You need to set up the followings:

1. Because the Canberra MCA uses the *.CNF file extension which file type is registered in the most Microsoft Windows version to an "modem file type", you need to delete this association (from the "Control Panel | Folder Options | File Types" list.)
2. The Excel2Genie is based on Visual Basic macros built in the Excel. You have to enable to run macros and the VBA modules in the MS Excel (you can change macro security settings in the "Preferences | Trust Center" menu item)

If you have any questions/comments email to: This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Download link:

Installation issues

Q1: Under which operating systems can I use BrainMOD?

A1: BrainMOD is currently (version 0.1.2) available for Ubuntu 12.04, Debian 6.0 Linux distributions and Windows 7. Windows Xp install kit is planned to be distributed soon.

Q2: How can I install BrainMOD on Linux?

A2: Follow these steps:

1. Add the following line to the end of / etc / apt / sources.list:

deb http://<USER>:<PASSW>@petdisk.atomki.hu/pkgs/ test bin
   where the fields <USER> and <PASSW> have to be replaced by the username and password received via e-mail.

2. Refresh the repository database:
    apt-get update

3. Install BrainMOD:
    apt-get install brainmod

4. Start BrainMOD software in command line:
    BrainMOD

Q3: How can I in install BrainMOD on Windows 7?

A3: Log in with your ENIAC username and password, click on this link, download and run the install kit BrainMODv0.1.2-w7.exe

Q4: How can I in intsall BrainMOD on Windows Xp?

A4: Sorry, there is currently no install kit for Windows Xp available. Check back later.

Q5: How can I install BrainMOD on 32 and 64 bit architectures?

A5: For Linux, currently only 64-bit package is available.

For Windows 7, the install kit works on both 32 and 64 bit systems.

Q6: Installation on Windows finished without any problems, but the software does not run.

A6: Try to install Microsoft Visual C++ 2008 Redistributable package.

Q7: Package installation on Ubuntu 12.04 finished without any problems, but the software keeps freezing. (Nvidia users)

A7: Switch off "Sync to VBlank" in the "OpenGL Settings" tab of the System -> preferences -> NVIDIA X Server Settings dialog.

T. Spisák, S.A. Kis, G. Opposits, I. Lajtos, L. Balkay, M. Emri

Department of Nuclear Medicine, Medical and Health Science Center, University of Debrecen, Debrecen, Hungary

Purpose of the software

Within the Central Nervous System Imaging project (http://www.eniac-csi.org/) of the ENIAC consortium, the need has emerged for a general multimodal visualization platform which facilitates the evaluation of data produced by new enhanced devices developed in the project. Taking advantage of multi-source post-processed data, this software aims to help interpreting complex intra-modal relationships. The modalities involved are PET, MRI, EEG, EIT.

According to the project proposal, our purpose was to develop a software for interactive user-friendly 2D and 3D visualization of post-processed multi-modal medical imaging data. Important requirements were to manage dynamic image data and explicitly support the use of various enhanced brain imaging techniques.

Methods / Implementation

The input of the software are MR structural data, fMRI and PET dynamic data and activation maps (GLM, ICA), EEG/EIT based static functional maps and dynamic data, other EEG and fMRI related time series (eg. hemodynamic response functions, independent component analysis time courses), volumes-of-interests of segmentation data and EEG/EIT marker positions. Besides conventional 2D image fusion features, the software provides numerous ways to reveal intra-modal dynamic relationships. Volumes-of-interests can be delineated manually or automatically aided by various segmentation algorithms or brain atlases [1]. Time series curves can be generated from the image data and on these various operations can be performed (eg. resampling, filters, correlation, convolution).

Three dimensional surfaces can be reconstructed, visualized and colored by multiple parameters (eg. dynamic functional information).

The program is built upon the MultiModal Medical Imaging software library system (www.minipetct.com/m3i) and runs on Windows 7 and Windows Xp operation systems and various Linux distributions. The hardware requirements of the application match the current average PC configurations used in medical image analysis.

The software system was implemented in C++.

Features illustrated at the exhibit

At the exhibit the features of the software are illustrated by performing a comparsion analysis of EEG-fMRI activation maps vs. resected area and evaluating the overlap between fMRI parametric maps computed by Independent Component Analysis and standard resting-state network templates [2].

References

[1] T. Spisák, M. Koselák, G. Opposits, S. A. Kis, L. Trón, A. Jakab, E. Berényi, M. Emri, Region management toolkit for atlas-space image processing, MAGMA 24 (S1):543, 2011.

[2] Shirer, WR and Ryali, S. and Rykhlevskaia, E. and Menon, V. and Greicius, MD,Decoding subject-driven cognitive states with whole-brain connectivity patterns, Cerebral Cortex, 22(1):158-162, 2012.

T. Spisák 1, G. Opposits 1, S. A. Kis 1, B. Clemens 2, M. Emri 1

1 Department of Nuclear Medicine, Medical and Health Science Center, University of Debrecen, Debrecen, Hungary

2 Department of Neurology, Kenézy Hospital Ltd., Debrecen, Hungary

PURPOSE OF THE SOFTWARE

Graph theory based structural and functional brain connectivity analysis is a novel method providing new insights into the dynamics and complexity of the brain by modeling it's regional interactions [1]. Due to the heterogeneity and dynamic development of the applied mathematical models and analysis techniques the software support of this field is still poorly accomplished [2].

Our purpose was to develop a user friendly software system dedicated for the analysis and visualization of multimodal brain connectivity data based on EEG, fMRI and DTI data.

METHODS/IMPLEMENTATION/HARDWARE REQUIREMENTS

The software system has modular architecture which provides the opportunity to rapidly follow the latest improvements of connectivity analysis and visualization methods by incremental development. Reconstruction of brain networks is modality dependent and can be performed with various state-of-the-art software tools, eg. BrainLOC (www.minipetct.com/brainloc) [3], Matlab and R for fMRI, FSL or Matlab softwares for DTI and NeuroGuide for EEG-LORETA data. These software tools can be easily fitted into the processing pipeline of the system. The resulting connectivity matrices can be displayed and thresholded interactively. Various interchangeable components are present for global (eg. small-worldness), modular (eg. community detection, modularity scores) and nodal (eg. various hub-scores) analysis of binary and weighted graphs in both individual and population level [4]. Cost-integration [5] technique was implemented to solve the problem of thresholding networks. Interpreting the results is aided by real-time 2D and 3D "galss brain" visualization techniques and various plots.

The program is built upon the MultiModal Medical Imaging (M3I) software library system (www.minipetct.com/m3i) and runs on Windows 7 and Windows Xp operation systems and various Linux distributions (www.minipetct.com/braincon). The hardware requirements of the application match the current average PC configurations used in medical image analysis.

The software system was implemented mainly in C++ and partly in R.

FEATURES ILLUSTRATED AT THE EXHIBIT

At the exhibit fMRI, EEG-LORETA and DTI based connectivity data analysis is demonstrated.

Different methods (like binary and weighted analysis) are evaluated on the same data, connectivity patterns and hub-scores corresponding to brain regions are visualized in 3D.

REFERENCES

[1] Sporns, O., The human connectome: a complex network, Annals of the New York Academy of Sciences, 1224(1):109-125, 2011.

[2] Leergaard, T.B. and Hilgetag, C.C. and Sporns, O., Mapping the Connectome: Multi-Level Analysis of Brain Connectivity, Frontiers in Neuroinformatics, 6, 2012.

[3] Spisák, T., Koselák, M., Opposits, G., Kis, SA., Trón, L., Jakab, A.,

Berényi, E., Emri, M., Region management toolkit for atlas-space image processing, MAGMA 24 (S1):543, 2011.

[4] Rubinov, M. and Sporns, O., Complex network measures of brain connectivity: uses and interpretations, Neuroimage, 52(3):1059-1069, 2010.

[5] Ginestet, C.E. and Nichols, T.E. and Bullmore, E.T. and Simmons, A., Brain network analysis: separating cost from topology using cost-integration, PloS one, 6(7):e21570, 2011.

The most important task of our group is the supervision of the quality management system in connection with the GMP conform radiopharmaceutical manufacturing activity running in our institute. This role not only involves the release of incoming materials and finished products, but also requires the maintenance of an up-to-date documentation system about manufacture, out of specification and deviations, change control and pharmacovigilance.

Furthermore, the Pharmaceutical Quality Assurance Group is responsible for any changes in any existing Marketing Authorisations and for the organisation of the registration procedure of novel radiopharmaceutical agents. Also, the head of the group is the contact person towards the National Institute for Quality- and Organisational Development in Healthcare and Medicines – National Institute of Pharmacy.

In the last 5 years the number of PET investigations had raised nearly tenfold, this year it is near to 12000. In the procedures [18F]FDG (2-[18F]fluoro-2-deoxy-D-glucose) is used in nearly 100 %. The use of a few times C-11 labelled methionine and acetate besides the FDG is negligible. In our country the technical conditions of PET radiopharmaceutical production are excellent. Two laboratories obtained production licence, and marketing authorizations for FDG and the above mentioned C-11 tracers. This makes possible to provide FDG not only for Hungary, but for the neighbouring countries (Romania, Serbia, Bulgaria) as well. The registered C-11 labelled tracers are used on the spot. In Debrecen the process of registration of C-11 labelled choline has been started.

The Multimodal Imaging Group staff is involved in the management of INM's computer systems and to coordinate a variety of activities directed towards the enhancement of INM's medical imaging portfolio.

Services

• Management of INM's personal computer system and computer controlled devices of GMP compatible Radiochemistry Laboratories.
• Management of Medical Imaging Servers including 50 core cluster, file and authentication servers and a high capacity backup system.
• Management of INM's email, web services and INM-wide network administration.
• Management of INM's DICOM server expanded by DicomBBox automated image processing software system. 
• Management of hardware and software of MiniPET lab and Biological Research labs.

 Image Processing and Software Development Projects

 Multimodal Imaging Software Distribution

• Maintaining and developing MultiModal Imaging (M3I) software library system and applications (BrainCAD, BrainLOC, BrainMOD, BrainCON, Virtuose etc. ) and support the distributed software (BrainCAD, BrainLOC).
• Implementing and developing C++ and R based tools for graph theoretical analysis for population level neuroimaging projects.
• Developing software system of the DICOM Server Based Automated Image Processing Service (DicomBBox) including CT-MRI, SPECT/PET-MRI registration, T1 based spatial normalization and T1 based automated regional analysis for functional data (PET, SPECT, fMRI, Loreta) 
• Maintaining and developing controlling software of in-house developed radiochemistry synthesis systems.

 MiniPET/CT

• Improving image quality of MiniPET scanner using hexagonal and non regular gridding 2D and 3D image reconstruction algorithms.
• Improving image quality of MiniPET scanner using special statistical methods in event processing algorithms.
• Adapting PET-image reconstruction and correction software onto High Performance Computing system.
• Developing Rat Brain Atlas for MiniPET  projects.
• Developing whole body small animal image registration methods for registering MiniPET images and MRI images acquired by human 1.5T - 3T MRI. 
• Extending MiniPET scanner with an flat-panel based small animal CT scanner. 

 Clinical Studies

• Applying graph theoretical analysis in clinical studies using EEG registrations. Collaborators: Dept. of Neurology, Kenézy Hospital 
• Applying graph theoretical analysis in clinical studies using resting state, activation fMRI and diffusion MRI images.Collabprators: Department of Biomedical Laboratory and Imaging Science
• Developing a network simulator for methodological validation of graph theoretical algorithms.
• Developing new method for checking the accuracy of high precision pathological CT-MRI registration using huge (more then 1000 subject) archived data. Collabprators: Department of Biomedical Laboratory and Imaging Science
• Validating our FDG-PET supported virtual bronhoscopy method and software. Collabprators: Josa A. Hospital, Scanomed Ltd.
• Developig a surface based registration method for diagnostic and low-dose chest CT registration.
• Validating a landmark based registration method for fused visualization of endocardial maps and MRI/PET images. Collabprators: Institute of Diagnostic Imaging and Radiation Oncology of the Kaposvár University
• Adapting image registration, spatial normalization, volumetric analysis and graph theoretical analysis software to running on High Performance Computing.

Selected Publications

• Clemens B., Puskás S., Bessenyei M., Emri M., Spisák T., Koselák M., Hollódy K., Fogarasi A., Kondákór I., Füle K., Fekete I. EEG functional connectivity of the intrahemispheric cortico-cortical network of idiopathic generalized epilepsy. Epilepsy Res, 2011. 96:11-23 
• Jakab A., Molnar P., Emri M., Berényi E. Glioma grade assessment by using histogram analysis of diffusion tensor imaging-derived maps. Neuroradiology, 2011. 53:483-491 
• Kovács A., Toth L., Glavák C., Liposits C., Hadjiev J., Antal G., Emri M., Vandulek C., Répa I. Integrating functional MRI information into conventional 3D radiotherapy planning of CNS tumors. Is it worth it? J Neuro-oncol, 2011.
• Gyöngyösi M., Hemetsberger R., Wolbank S., Kaun C., Posa A., Márián T., Balkay L., Emri M., Galuska L., Mikecz P., Petrási Z., Charwat S., Hemetsberger H., Blanco J., Maurer G. Imaging the Migration of Therapeutically Delivered Cardiac Stem Cells. Jacc Cardiovasc Imaging, 2010. 3:772-775 
• Kis S.A., Emri M., Opposits G., Bükki T., Valastyán I., Hegyesi G., Imrek J., Kalinka G., Molnár J., Novák D., Végh J., Kerék A., Trón L., Balkay L. Comparison of Monte Carlo simulated and measured parameters of miniPET scanner. Nucl Instrum Meth A, 2007. 571:449-452 
• Emri M., Glaub T., Berecz R., Lengyel Z., Mikecz P., Répa I., Bartók E., Degrell I., Trón L. Brain blood flow changes measured by positron emission tomography during an auditory cognitive task in healthy volunteers and in schizophrenic patients. Prog Neuro-psychoph, 2006. 30:516-520
• Hegyesi G., Imrek J., Kalinka G., Molnár J., Novák D., Végh J., Balkay L., Emri M., Kis S.A., Molnár G., Trón L., Valastyán I., Bagaméry I., Bükki T., Rózsa S., Szabó Z., Kerék A. Ethernet based distributed data acquisition system for a small animal PET. Ieee T Nucl Sci, 2006. 53:2112-2117 
• Honbolygo F., Csepe V., Fekésházy A., Emri M., Márián T., Sárközy G. Converging evidences on language impairment in Landau-Kleffner Syndrome revealed by behavioral and brain activity measures: A case study. Clin Neurophysiol, 2006. 117:295-305
• Emri M., Kisely M., Lengyel Z., Balkay L., Márián T., Mikó L., Berényi E., Sziklai I., Trón L., Tóth Á. Cortical Projection of Peripheral Vestibular Signaling. J Neurophysiol, 2003. 89:2639-2646

Selected Posters

• Automated region analysis of brain PET examinations (EANM11)
• Region management toolkit for atlas-space image processing (ESMRMB11)
• Digital brain atlas assisted localization software for individual and population analysis of SPECT and PET data (EANM11)
• Registration of low-dose and diagnostic chest CT scans based on skeletal and bronchus surface models
• MultiModal Medical Imaging software and services for research and education

Selected Presentations 

• BrainLOC
• Virtual Bronchoscopy
• Agyatlaszok 

Stuff and contact information ...

Aim: The Institute of Nuclear Medicine offers automated image registration services for partners via a DICOM server using an in-house developed image processing pipeline. During the development of BrainLOC software several utilities have been worked out to evaluate the automated regional analysis of spatial standardized MRI and PET data by using predefined region systems of more than 20 digitalized brain atlases. Our goal was to introduce a new service to support the automated region analysis of brain PET examinations for academic purposes.

Materials and Methods: We have used the MultiModal Medical Imaging software system to develop the main software components required by the automated regional analysis service: pre-defined functional and anatomical brain structures as part of the VOI database of the BrainLOC application; 3rd party (MNI, FSL) and in-house developed multimodal registration and standardization software; utilities for ROI analysis. We have also developed the DicomBBox software to receive and convert images, which is built on the basis of the DICOM server in our institute. Processing and monitoring services are available through the interfaces developed for the R+D web site of our institute.

Results: In contrast with our initial goals, a completely automated software system was developed to evaluate  regional analysis of brain PET data using customized regional definitions of various brain atlases. The user requesting this service could select regions from more than 20 brain atlases and for spatial standardization T1-weighted MRI or PET templates. The results of the analysis of the images received by our DICOM server can be accessed by email or through the web site of the institute. For validation 10 methionine-PET examinations were used. The standardization was carried out by the automated system and the fitted brain regions have been verified by two independent professionals. A nuclear medicine expert supervised the PET-MRI and a radiologist checked the CT-MRI fitting using the BrainLOC software.

Conclusion: By means of institutional infrastructure we have introduced a new service for clinical projects, which facilitates individual and population-based region analysis for institutes lacking the specific software and infrastructure. The service is available through our R+D web page and DICOM server.

Purpose of the software: Digital brain atlases offer a prominent solution for the anatomical localization of the physiological characteristics and pathological disorders of the brain investigated by MRI studies. The choice of the appropriate region system is a cardinal issue in various image processing tasks emerging by studies on relationships of brain structure, function or connectomes. The purpose of the presented sofware package is to afford a complex region management toolkit and provide the opportunity of constructing special, easily exportable region systems based on the regions of multiple brain atlases.

Methods/Implementations/Hardware Requirements: Using the multi-atlas framework developed in our institute, regions of various brain atlases can be collected and used simultanously. To merge these and optionally other user-defined regions to a uniform region system adaptable for arbitrary atlas-space image processing tasks some general and more specific set operations were implemented. The software is built upon the MultiModal Medical Imaging software library system (www.minipetct.hu) and runs on Windows 7 and Windows Xp operation systems and various Linux distributions. The hardware requirements of the application match the current average PC configurations used in medical image analysis.

Features illustrated at the exhibit: Our institutional brain connectivity research project is highly promoted by the presented system. At the exhibit the features of the software are presented by constructing multi-atlas based bilateralized region systems specially adaptable for brain connectivity analysis based on resting state fMRI and DTI data.

AIM Brain atlases offer a prominent solution for the anatomical localization of the physiological processes and pathological disorders of the brain investigated by cranial SPECT and PET studies. Although the number of the available brain atlases shows a significant growth, the support of this technique by information systems is still poorly accomplished.
The purpose of our work is to develop an interactive software assisted by multiple brain atlas databases for the promotion of the multi-modal medical imaging projects proceeded in our institute.

MATERIALS & METHODS To deal with the semantic and syntactic differences of the available databases a general atlas definition was constructed, which enables the uniform handling of various atlases. As part of this system we have developed components and database models for maintaining the discrete structural maps, the maximum probability maps and the region systems contained by the atlases. By implementing the deployed uniforming model, a framework was constructed, providing tools for the integration, maintenance and utilization of atlases in various tasks. A graphical user interface application, called BrainLOC, has also been developed to perform localization and region analysis tasks. The software is built upon the MultiModal Medical Imaging software development system.

RESULTS According to our purpose, a general and extendable model and framework for atlas uniforming has been developed. Based on these, the BrainLOC application (www.minipetct.com) was deployed. The software became one of the most important tools of several institutional projects, and among others it permits of the atlas-assisted anatomical localization and region analysis of SPECT and PET data aligned into atlas-space by the registration tool of the institutional automated image processing framework. The entire system was tested and validated with the PET and SPECT data of 20 subjects. BrainLOC is published under student and academic licenses for educational and research purposes.

CONCLUSION Using BrainLOC, the database of over 20 deterministic and probabilistic brain atlases can be used simultaneously for localization and region analysis tasks emerging by cranial PET and SPECT studies. Applying the appropriate atlas or an arbitrary collection of regions from different atlases provides the opportunity for the quantitative anatomical analysis of functional images.