基于深度学习的均衡优化算法在磁共振成像上的脑肿瘤分割与分类

IF 1 4区生物学 Q3 BIOLOGY

Brazilian Archives of Biology and Technology Pub Date : 2023-01-01 DOI:10.1590/1678-4324-2023220896

Hariharan Ramamoorthy, Mohan Ramasundaram, Raja Soosaimarian Peter Raj, Krunal Randive

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引用次数: 0

摘要

提出了一种用于脑肿瘤分割和分类的EOADL-BTSC技术。分两个阶段进行数据预处理，即基于CLAHE的对比度增强和颅骨剥离。针对医学图像分割问题，提出了一种基于UNet技术的注意力初始化EOA。采用基于CapsNet的特征提取和CRNN模型进行脑障碍分类。

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Equilibrium Optimization Algorithm with Deep Learning Based Brain Tumor Segmentation and Classification on Magnetic Resonance Imaging

HIGHLIGHTS Proposed an EOADL-BTSC technique for Brain Tumor Segmentation and Classification. Perform data preprocessing in two stages namely CLAHE based contrast enhancement and skull stripping. Developed EOA with Attention inception based UNet technique is developed for medical image segmentation. Employ CapsNet based feature extraction and CRNN model for brain disorder classification.

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