HYBRIDIZATION OF DILATED CNN WITH ATTENTION LINK NET FOR BRAIN CANCER CLASSIFICATION
Journal Title: International Journal of Data Science and Artificial Intelligence - Year 2024, Vol 2, Issue 02
Abstract
Brain tumours (BT) are highly prevalent and dangerous disease, have extremely short prognoses at the most malignant grade. Merging the MRI modes results in hybrid images with information that is used to classify tumours. The obtained images are luxurious to gain and hard to store, the diagnostic process consume a substantial amount of time. The magnetic resonance imaging (MRI) provides clean structural data, but it is time-consuming. To overcome these issues, a novel deep learning-based model is proposed for the early detection and classification of brain tumour from MRI images. Initially, the input images are pre-processed utilizing Clifford gradient to improve the quality of the image. Then, hybrid dilated CNN model (HD-CNN) is employed for extracting the features in the pre-processed brain image. Afterward, the extracted features are fed into the Attention Link Net model to classify the four cases of brain tumour. According to the test result, the proposed model has a 99.23% accuracy rate. The Attention Link Net high accuracy than Alex Net, Dense Net, and Res Net which obtains 0.15%,0.31%, and 0.25% while having a significantly lower computational cost than other networks. The proposed model improves overall accuracy by 2.35%,0.94%, and 2.42%, over the VGG19, DNN, and DCNN, respectively.
Authors and Affiliations
Cheepurupalli Raghuram, V. S. R. K. Raju Dandu, B. Jaison
Keywords
Related Articles
- EP ID EP734886
- DOI -
- Views 108
- Downloads 0
SAFE-ACID: A NOVEL SECURITY ASSESSMENT FRAMEWORK FOR IOT INTRUSION DETECTION VIA DEEP LEARNING
Internet of Things (IoT) intrusion detection is crucial for ensuring the security of interconnected devices in our digital world. With diverse devices communicating in complex networks, IoT environments face vulnerabilit...
BLOCK CHAIN ENABLED DATA SECURITY USING BLOWFISH ALGORITHM IN SMART GRID NETWORK
Smart Grid provides a reliable and efficient end-toend delivery system. Data on each user's unique electricity consumption is given in real time. It also enables utilities to control and monitor the electrical system in...
DYNAMIC LOAD BALANCING IN CLOUD COMPUTING USING HYBRID KOOKABURRA-PELICAN OPTIMIZATION ALGORITHMS
Cloud Computing (CC) technology facilitates virtualized computer resources to users via service providers. Load balancing assumes a critical role in distributing dynamic workloads across cloud systems, ensuring equitable...
IN-DEPTH EXPLORATION AND COMPARATIVE ASSESSMENT OF CUTTING-EDGE ALGORITHMS FOR IMPULSE NOISE ATTENUATION IN CORRUPTED VISUAL DATA
Image denoising is a vital process in image pre-processing, particularly for applications focused on image-based objectives. This process, which occurs during image acquisition and transmission, is crucial for enhancing...
CLASSIFICATION OF LIVER CANCER VIA DEEP LEARNING BASED DILATED ATTENTION CONVOLUTIONAL NEURAL NETWORK
Liver cancer occur when normal cells develop aberrant DNA alterations and reproduce uncontrollably. Patients with cirrhosis, hepatitis B or C, or both have an increased risk of developing the progressing stage of cancer....