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Published Paper Details:
Neural Network-Based Ischemic Brain Stroke Identification in MRI Brain Images
Authors
Balasaheb Shelake,Prathamesh Karatkar,Sanskar Ghule,Rohit Gaikwad,L.J. Deokate
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Keywords
Ischemic stroke, MRI (Magnetic Resonance Imaging), CNN (Convolutional Neural Network), Ischemic brain lesion, Stroke diagnosis, Medical image analysis, Neuroimaging, Deep learning
Abstract
- Ischemic stroke, a leading cause of disability and mortality worldwide, demands swift and accurate diagnosis for effective treatment. Magnetic Resonance Imaging (MRI) is pivotal in diagnosing ischemic strokes due to its high-resolution depiction of brain tissue abnormalities. Leveraging the capabilities of Convolutional Neural Networks (CNNs), this study proposes a novel approach for ischemic stroke identification in MRI brain images.
The proposed method involves pre-processing MRI scans to enhance image quality and extract relevant features. Subsequently, a CNN classifier is trained on a dataset comprising a diverse range of ischemic stroke patterns. The CNN model learns to distinguish between normal brain tissue and regions affected by ischemic strokes by capturing subtle image features indicative of stroke pathology.
Experimental evaluation demonstrates the effectiveness of the proposed CNN-based approach in accurately identifying ischemic strokes from MRI brain images. The model achieves high accuracy, sensitivity, and specificity in stroke detection, surpassing existing methods. Moreover, the proposed method exhibits robustness across different MRI scanners and imaging protocols, highlighting its potential for clinical deployment.
This research contributes to the advancement of automated ischemic stroke detection, facilitating prompt diagnosis and timely intervention. The proposed CNN-based approach holds promise for enhancing stroke management strategies, leading to improved patient outcomes and reduced healthcare burden. Further refinement and validation of the model in real-world clinical settings are warranted to realize its full potential in routine ischemic stroke diagnosis
IJCRT's Publication Details
Unique Identification Number - IJCRT2404768
Paper ID - 256319
Author type - Indian Author
Page Number(s) - g706-g711
Pubished in - Volume 12 | Issue 4 | April 2024
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No Of Downloads - 81
Author Country - India, 411033, Pune, Pune, 411033, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
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Balasaheb Shelake,Prathamesh Karatkar,Sanskar Ghule,Rohit Gaikwad,L.J. Deokate, "Neural Network-Based Ischemic Brain Stroke Identification in MRI Brain Images", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 4, pp.g706-g711, April 2024, Available at :http://www.ijcrt.org/papers/IJCRT2404768.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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