Segmentation and classification of brain tumors from MRI images based on adaptive mechanisms and ELDP feature descriptor

KR Reddy, R Dhuli - Biomedical Signal Processing and Control, 2022 - Elsevier
Generally, soft tissue information of the brain is analyzed using Magnetic Resonance
Imaging (MRI). An unusual growth of cells (tumor) in or around the brain may affect its …

Classification of brain tumours from MR images with an enhanced deep learning approach using densely connected convolutional network

RM Prakash, RSS Kumari, K Valarmathi… - Computer Methods in …, 2023 - Taylor & Francis
Brain cancer is one of the most leading causes of death in human beings. There are different
types of tumours affecting the brain and early diagnosis of them increases the survival rate …

Automated detection of brain tumor disease using empirical wavelet transform based LBP variants and ant-lion optimization

DO Patil, ST Hamde - Multimedia Tools and Applications, 2021 - Springer
Early detection of brain tumor is a challenging task that assists medical practitioners in
disease diagnosis. This article presents a computer-assisted brain tumor detection scheme …

Brain tumor segmentation of normal and lesion tissues using hybrid clustering and hierarchical centroid shape descriptor

R Shanker, M Bhattacharya - Computer Methods in Biomechanics …, 2019 - Taylor & Francis
Robust segmentation of the brain magnetic resonance (MR) images is extremely important
for diagnosing the tissues quantitatively. It is crucial to detect the changes caused by the …

Brain tumor recognition by an optimized deep network utilizing ammended grasshopper optimization

J Zhu, C Gu, L Wei, H Li, R Jiang, FR Sheykhahmad - Heliyon, 2024 - cell.com
Brain tumors are abnormal cell masses that can get originated in the brain spread from other
organs. They can be categorized as either malignant (cancerous) or benign (noncancerous) …

Gaussian hybrid fuzzy clustering and radial basis neural network for automatic brain tumor classification in MRI images

P Sathish, NM Elango - Evolutionary Intelligence, 2022 - Springer
Abstract Magnetic Resonance Imaging (MRI) is an emerging research area, employed
extensively in radiology for the diagnosis of various neurological diseases. Here, as the …

[PDF][PDF] Cuckoo Search Constrained Gamma Masking for MRI Image Detail Enhancement.

MK Ojha, A Rai, A Prakash, P Tiwari… - Traitement du …, 2022 - researchgate.net
Accepted: 22 July 2022 Nature-inspired algorithms are widely applied in the arena of image
enhancement for various optimization purposes. To address the optimization complexities in …

Cuckoo search constrained gamma masking for MRI image contrast enhancement

A Prakash, AK Bhandari - Multimedia Tools and Applications, 2023 - Springer
Poor quality images in Magnetic Resonance Imaging (MRI) may not provide enough
information for visual interpretation of the affected areas of the human body. Cuckoo Search …

[PDF][PDF] Generative deep belief model for improved medical image segmentation

P Balaji - Intell. Autom. Soft Comput, 2023 - cdn.techscience.cn
Medical image assessment is based on segmentation at its fundamental stage. Deep neural
networks have been more popular for segmentation work in recent years. However, the …

Identification of Intensive Oscillation Parameters of Power System Based on CS-CNN-GRU Network

T Yunxue, S Shuo, Z Haonian, X Shibiao… - Electric Power …, 2024 - Taylor & Francis
Broadband oscillations caused by power electronic devices contain a large number of high
harmonics and interharmonics, and the frequencies of these harmonic/interharmonic …