Sinha, A and Kumar, T (2024) Enhancing Medical Diagnostics: Integrating AI for precise Brain Tumour Detection. In: ICMLDE 2023, 23 November 2023through 24 November 2023, Dehradun, pp. 456-467.
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Abstract
Recent strides in artificial intelligence (AI) and deep learning techniques have propelled the development of an AI-powered brain tumour detection model. This study blends multilevel thresholding, neural network optimisation, and image preprocessing to craft a robust AI model capable of accurately categorising diverse brain tumour types and normal cases. Through rigorous testing with a comprehensive dataset of 1747 images, the model achieves an accuracy of 92. Its integration into a user-friendly smartphone app, MediScan, enhances accessibility and practicality. The app provides heatmap visualisations and generates diagnostic reports, supporting medical professionals in making swift decisions. The model prioritises interpretability enhancement and has the potential to cultivate collaboration between AI experts and medical practitioners, thus advancing the field of brain tumour detection and diagnosis. While promising, the model demands computational resources and diverse datasets. This research also highlights AI's potential to transform healthcare diagnostics, ensuring precise and efficient brain tumour identification. © 2024 Elsevier B.V.. All rights reserved.
| Item Type: | Conference Paper |
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| Publication: | Procedia Computer Science |
| Publisher: | Elsevier B.V. |
| Additional Information: | The copyright for this article belongs to the authors. |
| Keywords: | Brain; Convolutional neural networks; Deep learning; Diagnosis; Image enhancement; Learning systems; Medical imaging; Statistical tests; Tumors, Brain tumor detection; Brain tumors; Deep learning; Diagnostic accuracy; Image embedding; Medical diagnostics; Multilevel thresholding; Neural-networks; Smartphone apps; Tumour detection, Smartphones |
| Department/Centre: | Division of Mechanical Sciences > Department of Design & Manufacturing (formerly Centre for Product Design & Manufacturing) |
| Date Deposited: | 31 Jul 2024 04:56 |
| Last Modified: | 31 Jul 2024 04:57 |
| URI: | http://eprints.iisc.ac.in/id/eprint/85654 |
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