LEVERAGING THE DEEP LEARNING & CONVOLUTIONAL NEURAL NETWORK (CNNS) IN THE EFFICACIOUS DETECTION & DIAGNOSIS OF CEREBRAL TUMOUR
Arnav Kakar
Abstract
To detect and distinguish brain tumour from medical images an app called tumour detection in being developed using advance ai techniques. This app allows healthcare professional to rapidly and precisely analyse brain tumour essentially providing patient's better medication. This user-friendly app is designed in such a way that a user can easily upload and analyse images. In a short span of time the application can deliver highly précised outcome. Radionics and morphometric features are utilized in the evaluation of medical images. In light of the rising prevalence of brain tumours, the Brain Tumour Detection App has the potential to revolutionize the way these complicated conditions are diagnosed and treated, raising the standard of care offered to patients worldwide. The application is made to be very efficient and easy to use. The application is intended for direct use by doctors, allowing them to quickly and precisely identify a brain tumour in a medical image.
References
- A smartphone-based system for brain tumor detection using deep learning' by N. Kim, J. Park, and K. Lee (2018).
- 'MobileNetV2 based brain tumor detection using a smartphone' by S. Rana, A. Sarma, and S. K. Singh (2020).
- 'A smartphone-based deep learning platform for detecting brain tumors using an ensemble of 3D convolutional neural networks' by J. Song et al. (2019).
- 'Mobile-based deep learning framework for brain tumor classification and segmentation' by S. S. Gajbhiye et al. (2019).
- “A mobile phone application for the detection of brain tumors using deep learning' by J. Du et al. (2019).
- 'Brain tumor detection using a smartphone and deep learning algorithms' by K. Sundararajan et al. (2020).
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