Brain Tumor Classification using Convolutional Neural Network
T. R. Ganesh Babu, V. Varsha, T. Santhi Sri, Shweta Kumari
Abstract
This study intuitively addresses a crucial need in the medical domain by introducing a customized Mobile-Net model for classifying brain cancer in medical imaging data. The paramount importance of accurate classification in cancer diagnosis and treatment planning cannot be emphasized further. This particular research primarily focuses on the practical application of semantic classification techniques to precisely identify and outline brain cancer zones in medical imaging data. By utilizing a Mobile-Net architecture, the developed model highlights outstanding performance with an accuracy score of 85%.
Topics & Concepts
Convolutional neural networkComputer scienceArtificial intelligenceBrain cancerDomain (mathematical analysis)Medical imagingArtificial neural networkMachine learningArchitectureNeuroimagingContextual image classificationCancerData scienceImage (mathematics)MedicineNeuroscienceGeographyPsychologyArchaeologyMathematical analysisMathematicsInternal medicineBrain Tumor Detection and ClassificationCOVID-19 diagnosis using AIMachine Learning and ELM