Brain Tumor Detection Using U-Net Architectures in Industry 4.0 IoT Healthcare industries
Cancer involves the uncontrolled growth and spread of abnormal cells. Normally, cell growth, division, and death are regulated, but disruptions can lead to tumors [1]. Tumors can be benign or malignant; malignant tumors invade nearby tissues and can spread. Over 100 types of cancer are named after their tissue or organ of origin. Benign tumors, like meningiomas and pituitary tumors, grow slowly and rarely spread. Malignant tumors, such as astrocytomas and glioblastomas, are aggressive and hard to treat. Our study focuses on diagnosing three brain conditions: meningiomas, common noncancerous brain tumors in women; pituitary adenomas, slow-growing benign tumors; and gliomas, including astrocytomas and glioblastomas, which vary in aggressiveness [2].
Authors
- Mohsen Asghari Ilani (ORCID: https://orcid.org/0000-0003-0189-6956)
- Yaser Mike Banad (ORCID: https://orcid.org/0000-0001-7339-810X)
Institutions
- University of Oklahoma (US)
Publication Details
- Published
- 2024-09-30
- DOI
- https://doi.org/10.1109/aixset62544.2024.00022
- Citations
- 3
- Primary Topic
- Brain Tumor Detection and Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.74