Earlier Stage Identification of Bone Cancer with Regularized ELM

Title

Earlier Stage Identification of Bone Cancer with Regularized ELM

Creator

Murugesan S.; Sharma N.; Jayalakshmi N.; Pant K.; Chauhan A.; Acharjee P.B.

Description

A major focus of current research in the field of image processing is the application of such methods to the field of medical imaging. While dealing with biological issues like fractures, canoers, ulcers, etc., image processing facilitated pinpointing the precise cause and tailoring a remedy. In the field of tumor identification, medical imaging has set a new standard by overcoming a number of challenges. Medical imaging is the practice of generating images of the human body for diagnostic or exploratory purposes. Because of its high image quality, MRI is the method of choice for detecting tumors. This research study proposes the integration of RLM to detect tumors and presents an automatic bone cancer detection system to assist oncologists in making early diagnosis of bone malignancies, which in turn allows patients to receive treatment as soon as possible. This research work also proposes to detect bone tumors by using a combination of the RELM based M3 filtering, Canny Edge segmentation, and the Enhanced Harris corner approach. When compared to other models like CNN, ELM, and RNN, the suggested technique achieves an accuracy of around 97.55%. 2023 IEEE.

Source

Proceedings of the 7th International Conference on Intelligent Computing and Control Systems, ICICCS 2023, pp. 1849-1854.

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Canny Edge Detection; Improved Harris Corner Detection; Regularized Extreme Learning Machine (RELM)

Coverage

Murugesan S., R.M.D Engineering College, Kavaraipettai, Tamilnadu, Tiruvallur, India; Sharma N., Lovely Professional University, Department of Physical Education, Punjab, India; Jayalakshmi N., PSNA College of Engineering and Technology, Tamilnadu, Dindigul, India; Pant K., Graphic Era Deemed to Be University, Department of Biotechnology, Uttrakhand, Dehradun, India; Chauhan A., CHRIST (Deemed to Be University), Department of Life Sciences, Karnataka, Bengaluru, India; Acharjee P.B., CHRIST University, Computer Science, Maharashtra, Pune, India

Rights

Restricted Access

Relation

ISBN: 979-835039725-3

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICICCS56967.2023.10142670

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85163833300&doi=10.1109%2fICICCS56967.2023.10142670&partnerID=40&md5=a3f783e2dac007237fe41c784bf6838c