Publication Type: Edited Book
MACHINE LEARNING FOR BRAIN TUMOR IDENTIFICATION: PROGRESS AND BOTTLENECKS
Book Name: Futuristic Trends in Computing Technologies and Data Sciences Volume 3 Book 7
Authors: Mr. D. Anil Kumar, Mr. A. Sandeep Kumar, Mrs. K. Niveditha, Mr. Venkata Srinivasu Veesam
Keywords: Brain Tumor, Medical Imaging, Therapy, Important procedure, Precise diagnosis
Area/Stream: Computing Technologies and Data Sciences / Information and Knowledge Engineeringomputing and Communication / Others
Published in: IIP Series
Volume: 3, Month:May,Year:2024
Page No.: 131-138
e-ISBN: 978-93-6252-212-2
DOI/Link: https://www.doi.org/10.58532/V3BKCT7P1CH12
Abstract:
The integration of Artificial Intelligence (AI) in the field of medical imaging has shown promising potential for revolutionizing the detection and diagnosis of brain tumors. Recent years have witnessed significant strides in the application of AI algorithms, particularly convolutional neural networks (CNNs), for the auto-mated analysis of neuroimaging data. These algorithms demonstrate remarkable proficiency in recognizing subtle anomalies within MRI, CT, and PET scans, enabling earlier and more accurate identification of brain tumors. Furthermore, AI-powered systems can classify tumors into distinct categories, aiding clinicians in treatment planning and prognosis assessment. This paper explores the advancements and challenges of AI-driven approaches to the detection and classification of brain tumors. The study investigates advanced AI methods, such as deep learning, and shows how effective they are when compared to traditional methods. The potential impact of AI on neuro-oncology is underlined, along with the ethical and governmental repercussions of its use in therapeutic settings.
Cite this: Mr. D. Anil Kumar, Mr. A. Sandeep Kumar, Mrs. K. Niveditha, Mr. Venkata Srinivasu Veesam,"MACHINE LEARNING FOR BRAIN TUMOR IDENTIFICATION: PROGRESS AND BOTTLENECKS", Futuristic Trends in Computing Technologies and Data Sciences Volume 3 Book 7,IIP Series, Volume 3, May, 2024, Page no.131-138, e-ISBN: 978-93-6252-212-2, DOI/Link: https://www.doi.org/10.58532/V3BKCT7P1CH12
