Volume 16, Issue 4 (July & August 2025)
BCN 2025, 16(4): 701-714 |
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Jaber H, Aljobouri H, Koçak O M, Algin O, Çankaya I. Integrated MATLAB Toolbox for fMRI Visualization and Data Conversion. BCN 2025; 16 (4) :701-714
URL: http://bcn.iums.ac.ir/article-1-1418-en.html
URL: http://bcn.iums.ac.ir/article-1-1418-en.html
1- Department of Biomedical Engineering, College of Engineering, Al-Nahrain University, Baghdad, Iraq. & National MR Research Center (UMRAM), Bilkent University, Ankara, Turkey. & Department of Electrical and Electronics Engineering, Graduate School of Natural Sci., Ankara Yıldırım Beyazıt University, Ankara, Turkey.
2- Department of Biomedical Engineering, College of Engineering, Al-Nahrain University, Baghdad, Iraq. & Department of Electrical and Electronics Engineering, Graduate School of Natural Sci., Ankara Yıldırım Beyazıt University, Ankara, Turkey.
3- Department of Psychiatry, Medical School, Psychiatry Clinic, Başkent University, Ankara, Turkey.
4- National MR Research Center (UMRAM), Bilkent University, Ankara, Turkey. & Interventional MR Clinical R&D Institute, Ankara University, Ankara, Turkey. & Department of Radiology, Faculty of Medicine, Ankara University, Ankara, Turkey.
5- Department of Electrical and Electronics Engineering, Graduate School of Natural Sci., Ankara Yıldırım Beyazıt University, Ankara, Turkey.
2- Department of Biomedical Engineering, College of Engineering, Al-Nahrain University, Baghdad, Iraq. & Department of Electrical and Electronics Engineering, Graduate School of Natural Sci., Ankara Yıldırım Beyazıt University, Ankara, Turkey.
3- Department of Psychiatry, Medical School, Psychiatry Clinic, Başkent University, Ankara, Turkey.
4- National MR Research Center (UMRAM), Bilkent University, Ankara, Turkey. & Interventional MR Clinical R&D Institute, Ankara University, Ankara, Turkey. & Department of Radiology, Faculty of Medicine, Ankara University, Ankara, Turkey.
5- Department of Electrical and Electronics Engineering, Graduate School of Natural Sci., Ankara Yıldırım Beyazıt University, Ankara, Turkey.
Abstract:
Introduction: Working with functional magnetic resonance imaging (fMRI) often involves engaging with multiple file formats and complex viewers. In this study, we developed a novel platform as a visualization and conversion fMRI (VCfMRI) MATLAB toolbox for fMRI data.
Methods: The VCfMRI was developed to read and write 3D fMRI volumes in DICOM, NIfTI, ANALYZE, and MAT formats and convert between them, on a single user-friendly platform. It includes 62 functions across seven graphical user interface modules for conversion, batch read/write, and orthogonal viewing (sagittal, coronal, horizontal). This toolbox also supports overlaying statistical maps on anatomical images with adjustable thresholds. We built and tested VCfMRI using real datasets from a scanner (3T, Siemens Co.) at UMRAM, Bilkent University.
Results: VCfMRI successfully converted and visualized all supported formats in one environment, enabling synchronized 3D views and functional overlays with interactive threshold control, streamlining previously fragmented steps.
Conclusion: The VCfMRI toolbox provides a simple and efficient solution for fMRI data conversion and visualization. It simplifies the handling of fMRI datasets across different formats, which is especially beneficial for physicians, healthcare specialists, and researchers who face challenges in processing and visualizing multi-format neuroimaging data.
Methods: The VCfMRI was developed to read and write 3D fMRI volumes in DICOM, NIfTI, ANALYZE, and MAT formats and convert between them, on a single user-friendly platform. It includes 62 functions across seven graphical user interface modules for conversion, batch read/write, and orthogonal viewing (sagittal, coronal, horizontal). This toolbox also supports overlaying statistical maps on anatomical images with adjustable thresholds. We built and tested VCfMRI using real datasets from a scanner (3T, Siemens Co.) at UMRAM, Bilkent University.
Results: VCfMRI successfully converted and visualized all supported formats in one environment, enabling synchronized 3D views and functional overlays with interactive threshold control, streamlining previously fragmented steps.
Conclusion: The VCfMRI toolbox provides a simple and efficient solution for fMRI data conversion and visualization. It simplifies the handling of fMRI datasets across different formats, which is especially beneficial for physicians, healthcare specialists, and researchers who face challenges in processing and visualizing multi-format neuroimaging data.
Keywords: Brain imaging, Information systems, Functional magnetic resonance imaging (fMRI), Medical informatics computing
Type of Study: Original |
Subject:
Computational Neuroscience
Received: 2019/01/30 | Accepted: 2019/08/1 | Published: 2025/07/1
Received: 2019/01/30 | Accepted: 2019/08/1 | Published: 2025/07/1
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