A Review : Brain tumor detection using Digital Image Processing-Reference-Cited by-同舟云学术

A Review : Brain tumor detection using Digital Image Processing

Published:2023-03-01 Issue: Volume: Page:61-65
ISSN:2456-3307
Container-title:International Journal of Scientific Research in Computer Science, Engineering and Information Technology
language:en
Short-container-title:IJSRCSEIT

Author:

Dinesh M. Barode ¹,Rupali S. Awhad ¹,Seema S. Kawathekar ²

Affiliation:

1. Research Scholar, Department of Computer Science & Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India

2. Assistant Professor, Department of Computer Science & Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra, India

Abstract

Now a day, one of the most common diseases is a brain tumor. The challenge is to identify a tumor at an early stage, which is essential to receiving good care and surviving brain cancer patients. In the human body, the uncontrolled growth of cells is called a brain tumor. They have different types and characteristics and have different treatments. Medical imaging techniques play an important role in the detection of brain tumors. Although MRI (Magnetic Resonance Imaging) is frequently regarded as the best method for identifying this type of tumor, it has several drawbacks, and MRI images are more sensitive to ambient noise and other disruptions. As a result, it is challenging for doctors to identify the tumor and its origin.

Publisher

Technoscience Academy

Subject

General Medicine

Reference17 articles.

1. Borole VY, Nimbhore SS, Kawthekar DS. Image processing techniques for brain tumor detection: A review. International Journal of Emerging Trends & Technology in Computer Science (IJETTCS). Volume4Issue5(2), 2015 Sep; 4(5):2. http://www.ijettcs.org/Volume4Issue5(2)/IJETTCS-2015-10-01-7.pdf

2. Vipin Y. Borole, Seema S. Kawathekar, Study of various DIP Techniques used for Brain Tumor detection and tumor area calculation using MRI images, International Journal of Computer Sciences and Engineering, Vol.4, Issue.7, pp.39-43, 2016. https://www.ijcseonline.org/pdf_paper_view.php?paper_id=997&6-IJCSE-01741.pdf

3. D. Moitra, R. Mandal , Review of Brain Tumor Detection using Pattern Recognition Techniques, International Journal of Computer Sciences and Engineering, Vol.5, Issue.2, pp.121-123, 2017. https://www.ijcseonline.org/pdf_paper_view.php?paper_id=1189&21-IJCSE-15-2017.pdf

4. Vishal S. Shirsat, Seema S. Kawathekar, 2014, Classification of Brain Cancer Detection by using Magnetic Resonance Imaging, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) Volume 03, Issue 02 (February 2014), https://www.ijert.org/classification-of-brain-cancer-detection-by-using-magnetic-resonance-imaging#cite

5. Takizawa D, Mizumoto M, Yamamoto T, Oshiro Y, Fukushima H, Fukushima T, Terunuma T, Okumura T, Tsuboi K, Sakurai H. A comparative study of dose distribution of PBT, 3D-CRT and IMRT for pediatric brain tumors. Radiation oncology. 2017 Dec; 12:1-7. https://link.springer.com/article/10.1186/s13014-017-0775-2