Smart Skin Cancer Diagnosis: Integrating SCA-RELM Method for Enhanced Accuracy
- Title
- Smart Skin Cancer Diagnosis: Integrating SCA-RELM Method for Enhanced Accuracy
- Creator
- Subramanian M.; Taley R.A.; Sampath V.; Kartheeban K.; Palanimuthu K.; Acharjee P.B.
- Description
- One out of three cancers now is skin cancer, a figure that has exploded in the previous several decades. Melanoma is the worst kind of skin cancer and occurs in 4% of cases. It is also the most aggressive type. The health and economic impact of skin cancer is substantial, especially given its rising incidence and fatality rates. However, with early detection and treatment, the 5-year survival rate for skin cancer patients is much improved. As a result, a lot of money has gone into studying the disease and developing methods for early diagnosis in the hopes of stopping the rising tide of cancer cases and deaths, particularly melanoma. In order to enhance non-invasive skin cancer diagnosis, this research examines a range of optical modalities that have been utilized in recent years. The suggested system uses image processing to identify, remove, and categorize lesions from dermoscopy images; this system will greatly aid in the detection of melanoma, a type of skin cancer. A median filter is employed for preprocessing. Using watershed and clever edge detector, it can segment objects. The BOF plus SURF method is employed for feature extraction. It employs SCA-RELM, which performs better than the other two conventional approaches, to train the model. 2024 IEEE.
- Source
- 2024 3rd International Conference for Innovation in Technology, INOCON 2024
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- Bag of Feature (BoF) and Speeded Up Robust Features (SURFs); Regularized Extreme Learning Machine (RELM); Sine Cosine Algorithm (SCA)
- Coverage
- Subramanian M., Sri Sairam Engineering College, Department of Electronics and Instrumentation Engineering, Chennai, India; Taley R.A., College of Engineering and Technology, Maharashtra, Akola, India; Sampath V., Sri Sankara Arts and Science College (Autonomous), Department of Biochemistry, Kanchipuram, India; Kartheeban K., Kalasalingam Academy of Research and Education, Department of CSE, Krishnankoil, Anandnagar, India; Palanimuthu K., Institute of Health Sciences, Pediatric and Child Health Nursing, Dambi Dollo, Ethiopia; Acharjee P.B., Christ University, Pune Lavasa Campus, Karnataka, Bengaluru, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835038193-1
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Subramanian M.; Taley R.A.; Sampath V.; Kartheeban K.; Palanimuthu K.; Acharjee P.B., “Smart Skin Cancer Diagnosis: Integrating SCA-RELM Method for Enhanced Accuracy,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 24, 2025, https://archives.christuniversity.in/items/show/19447.