Artificial Intelligence and Deep Learning Based Brain Tumor Detection Using Image Processing

Title

Artificial Intelligence and Deep Learning Based Brain Tumor Detection Using Image Processing

Creator

Rajesh S.M.; Chiranmai I.; Jayapandian N.

Description

In the field of medical science, applications that are particularly used for diagnostic purposes, are used in the detection of brain tumors since detecting an error in MRI scanning is becoming a major task for radiologists and requires a lot of their focus. Flaws that are prevalent during tumor detection must be taken care of to avoid further complications. MRI scanning is one of the most recently developing technologies. The radiologist is a key player in the identification of the brain tumor. Radiologists have to check every image perfectly to avoid the errors in identifying the brain tumor. There is a probability that sometimes cerebral fluid may also appear as mass tissue during the MRI scan. The model that is proposed in this research uses a machine learning algorithm which helps to improve the validity of the classification of the images that are taken in MRI scans. The study focuses on having an automated system that carries out an essential role in determining whether a lump is present in the brain or not. The study tries to resolve the primary flaws in detection necessary to evade further complications in MRI images in brain detection. The main aim of this study is to train the algorithm in a more extensive dataset and to check the patient-level validity with the help of various new datasets. 2023 IEEE.

Source

Proceedings of the 5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023, pp. 244-248.

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Artificial Intelligence; Brain Tumor; Convolutional Neural Network; Deep Learning; MRI (Magnetic Resonance Imaging) Scanning; Support Vector Machine

Coverage

Rajesh S.M., Christ (Deemed to Be University), Department of Cse, India; Chiranmai I., Christ (Deemed to Be University), Department of Cse, India; Jayapandian N., Christ (Deemed to Be University), Department of Cse, India

Rights

Restricted Access

Relation

ISBN: 979-835032142-5

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICIRCA57980.2023.10220659

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85172182485&doi=10.1109%2fICIRCA57980.2023.10220659&partnerID=40&md5=dffe8b0fde9c34a36994a6eb4d78ac96