Work

Brain Tumor Detection and Classification Using Fine-Tuned CNN with ResNet50 and EfficientNet

Year: 2024

Type: article

Abstract: Accurate and timely diagnosis of brain tumors is critical for successful treatment of the disease. Early detection not only aids in the development of better medication, but it can also save a life in the long run. The domain of brain tumor analysis has efficiently applied medical image processing ideas, particularly on MR images. This paper presents segmentation using Convolutional Neural Networks (CNN) architecture with ResNet50 and EfficientNet as backbones on the Figshare data set, with an accuracy level of 0.xxx.

Source: International Journal of Informatics and Computation

DOI: 10.35842/ijicom.v6i1.80

Author: Muhammad Ali Sultan

Institution: Mercu Buana University

Language: English

Topic: Brain Tumor Detection and Classification

Subfield: Neurology

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W4404334567

FWCI: 0.135

Cites:

Cited by: 1

Related to: 10