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Showing 2 results for Brain Neoplasm
A new method for brain tumor detection using the Bhattacharyya similarity coefficient, color conversions and neural network
Bahman Mansori , Abdol Hamid Pilevar , Babak Azadnia ,
Volume 73, Issue 7 (10-2015)
Abstract

Background: Magnetic resonance imaging (MRI) is widely applied for examination and diagnosis of brain tumors based on its advantages of high resolution in detecting the soft tissues and especially of its harmless radiation damages to human bodies. The goal of the processing of images is automatic segmentation of brain edema and tumors, in different dimensions of the magnetic resonance images. Methods: The proposed method is based on the unsupervised method which discovers the tumor region, if there is any, by analyzing the similarities between two hemispheres and computes the image size of the goal function based on Bhattacharyya coefficient which is used in the next stage to detect the tumor region or some part of it. In this stage, for reducing the color variation, the gray brain image is segmented, then it is turned to gray again. The self-organizing map (SOM) neural network is used the segmented brain image is colored and finally the tumor is detected by matching the detected region and the colored image. This method is proposed to analyze MRI images for discovering brain tumors, and done in Bu Ali Sina University, Hamedan, Iran, in 2014. Results: The results for 30 randomly selected images from data bank of MRI center in Hamedan was compared with manually segmentation of experts. The results showed that, our proposed method had the accuracy of more than 94% at Jaccard similarity index (JSI), 97% at Dice similarity score (DSS), and 98% and 99% at two measures of specificity and sensitivity. Conclusion: The experimental results showed that it was satisfactory and can be used in automatic separation of tumor from normal brain tissues and therefore it can be used in practical applications. The results showed that the use of SOM neural network to classify useful magnetic resonance imaging of the brain and demonstrated a good performance.


Comparative study of electrocardiogram changes in patients with brain tumors with midline shift and without midline shift
Majid Zamani, Masoudeh Babakhanian , Farhad Heydari , Mohammad Nasr-Esfahani , Mohammad Mahdi Zarezadeh ,
Volume 80, Issue 7 (10-2022)
Abstract
Background: In addition to heart disease, ECG also changes in non-heart disease, which due to its similarity, can lead to misdiagnosis of heart disease in patients. ECG changes in brain lesions such as ischemic and hemorrhagic strokes, brain traumas, etc. and have been studied in many articles, but the effects of brain midline shift on ECG changes have not been studied. In this study, we want to examine these changes.
Methods: This is a prospective cross-sectional descriptive study. Patients with brain tumors who were referred to Al-Zahra and Kashani hospitals in Isfahan from April 2019 to March 2021 were selected. Patients with a history of heart disease, patients receiving medications that cause ECG changes, patients with ECG changes due to non-cardiac and cerebral causes, and individuals under 15 years of age were not included in the study. Patients whose ECG changes were due to electrolyte disturbances or acute heart problems were also excluded from the study. After obtaining informed consent from patients, a CT scan or brain MRI was taken and patients were divided into two groups with and without midline shift. Then the ECG was taken and ECG changes (T wave, ST segment, QTc Interval, QRS prolongation) were compared in two groups of brain tumors with and without midline shift.
Results: 136 patients were included in the study. Of these, 69 patients were in the without midline shift group and 67 patients were in the midline shift group. In the midline shift group, 3% of patients had ST segment changes and 23.9% had T wave changes, which were 1.4% and 10.1% in the without midline shift group, respectively. The mean QTc Interval in the two groups without and with midline shift was 338.26 (4 28.438) and 388.66 (37.855), respectively, and the mean QRS in the without midline shift group was 86.09 (88.9.88) ms and in the midline shift group was 94.63 (±12.83) ms.
Conclusion: Brain midline shifts can cause QRS widening, QTc interval prolongation, and T-wave changes in patients' ECGs.

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