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Start Over Topic brain tumors Publication Year Range Last 3 years Region baghdad (iraq)
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1. Automated brain tumor detection of MRI image based on hybrid image processing techniques.

Author

Salman, Lina A., Hashim, Ashwaq T., and Hasan, Ahmed M.

Subjects
*BRAIN tumors, *IMAGE processing, *MAGNETIC resonance imaging, *MAGNETIC resonance, *TEACHING hospitals, *IMAGE enhancement (Imaging systems)
Abstract

Primary challenges are the identification, segmentation, and extraction of the afflicted area from the scanning of magnetic resonance. However, it is a time-consuming and tiresome for clinical specialists. In this paper, an automated brain tumor system is proposed. The proposed system employs hybrid image processing techniques such as contrast correction, histogram normalization, thresholding techniques, arithmetic, and morphological operations to quarantine nearby organs and other tissue from the brain for improving the localization of the affected region. At first, the skull stripping process is proposed to segregate the non-designated regions to extract the designated brain regions. Those resultant brain region images are further subjected to discover the brain tumor. The planned scheme is studied on the magnetic resonance (MR) images with the use of T1, T2, T1c, and fluid-attenuated inversion recovery (FLAIR). The proposed hybrid method employed. The results reveal that the proposed method is quite efficient to extract the tumor region. The accuracy rate for segmentation and separation of area of interest in brain tumor reached to 95%. Finally, the significance of the proposed procedure is confirmed using the real image clinical dataset got from ten patients were diagnosed as begin, malignant, and metastatic brain tumors in Al-Yarmouk and Baghdad teaching hospital in Baghdad, Iraq. [ABSTRACT FROM AUTHOR]

Published
2022
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2. Study Results from University of Technology in the Area of Brain Cancer Reported (Advances In Brain Tumor Segmentation and Skull Stripping: a 3d Residual Attention U-net Approach).

Subjects
SKULL tumors, BRAIN tumors, BRAIN cancer, MAGNETIC resonance imaging, RESEARCH personnel
Abstract

A recent study conducted by researchers at the University of Technology in Baghdad, Iraq, has developed a new model for brain tumor segmentation and skull stripping in Magnetic Resonance Imaging (MRI). The model, called the 3D_Att_Res_U-Net, combines attention mechanisms and residual units to improve the accuracy of tumor segmentation. The researchers trained the model using the Brain Tumor Segmentation (BraTS) 2020 dataset and achieved high Dice Similarity Coefficients (DSC) for skull stripping and tumor segmentation. The study concludes that the proposed approach is superior to existing methods in this research domain. [Extracted from the article]

Published
2023