A multiscale morphological segmentation and classification of brain tumor using supervised learning algorithm

• Published in: AIP conference proceedings Vol. 2966; no. 1
• Main Authors: Krishnan, Pavihaa Lakshmi Babu Muthu, Sampath, Vidhya
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Melville American Institute of Physics 26.03.2024
• Subjects: Algorithms; Brain; Brain cancer; Datasets; Discrete cosine transform; Fourier transforms; Image segmentation; K-nearest neighbors algorithm; Lesions; Machine learning; Magnetic resonance imaging; Medical imaging; Morphology; Noise reduction; Supervised learning; Support vector machines; Tumors

A Brain tumor segmentation and classification method is developed using K-nearest neighbor (KNN), a supervised machine learning algorithm for classification to classify the tumor types. The input dataset is filtered using bilateral filtering by preserving edges and reducing noise. The gray level ima...