International Journal of Radiation Research

en Differentiation of metastatic and primary brain tumor using magnetic resonance imaging Radiation Biology Radiation Biology تحقيق بديع Original Research <div style="text-align: justify;">Background: Brain tumor segmentation is an important aspect of medical image processing. Timely detection of brain tumors can increase a patient's survival rate significantly. Doctors use traditional manual techniques for diagnosis, but these techniques are tedious and require intricate programming. Materials and Methods: New developments of automatic and semi-automatic approaches for image processing have been applied. MRI images are characterized using segmentation and registration Toolkit (ITK-SNAP) software to find and demarcate boundaries and assess brain tumor volume from MRI images. This study included six untreated brain tumor patients (aged 35-75) to explore the feasibility of using semi-automated MRI techniques for tumor segmentation. Despite the small sample size, the method showed promising accuracy, highlighting its potential for clinical use. Results: Our findings revealed accurate diagnosis of primary brain tumors, 3D tumor size, tumor edges, and metastatic brain tumors based on MRI images. ITK-SNAP proved to be more effective for diagnosing metastatic and secondary brain tumors than conventional techniques. The importance of effective and accurate segmentation, particularly discrimination among primary and metastatic tumors, was highlighted. Conclusion: On the contrary, completely automatic approaches tend to be imprecise. Tailoring the ITK-SNAP tool for brain tumor segmentation maximizes efficiency with improved accuracy for differentiating tumor categories.</div> Primary brain tumors, metastatic brain tumors, MRI, semi-automated segmentation, computer-assisted image interpretation. 259 265 http://ijrr.com/browse.php?a_code=A-10-1-1484&slc_lang=en&sid=1 M. Yasir 7900319475328460033012 7900319475328460033012 No Biophotonic Imaging Techniques Laboratory, Institute of Physics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan F. Siddique 7900319475328460033013 7900319475328460033013 No Department of Physics, Lahore Garrison University, Sector C, DHA Phase 6, Lahore, Pakistan F. Andleeb 7900319475328460033014 7900319475328460033014 No Department of Physics, Govt Sadiq Women University of Bahawalpur, Pakistan G. Gilanie 7900319475328460033015 7900319475328460033015 No Department of Artificial Intelligence, Faculty of Computing, The Islamia University of Bahawalpur, Bahawalpur, Pakistan H. Ullah hafeezullah@iub.edu.pk 7900319475328460033016 7900319475328460033016 No Biophotonic Imaging Techniques Laboratory, Institute of Physics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan