Advanced Cervical Lesion Detection using Deep Learning Techniques
- Title
- Advanced Cervical Lesion Detection using Deep Learning Techniques
- Creator
- Mukku L.; Thomas J.
- Description
- Cervical cancer has been one of the common causes for mortality by cancer in women across the world. But there are currently not enough skilled colposcopists, and the training process is drawn out. This implicates that there is a significant scope for artificial intelligence based computational models for segmentation of colposcope images. This paper proposes a segmentation network to accurately segment the cervix region and acetowhite lesions in a cervigram. This research can lay a foundation for research aiming to classify the cervix malignancy using AI. The method performed with a precision of 0.73870.1541, accuracy of 0.9291, recall of 0.79120.1439, a dice score of 0.74310.1506 and specificity of 0.95890.0131. The results prove that the model is reliable and robust. 2024 IEEE.
- Source
- 2024 1st International Conference on Communications and Computer Science, InCCCS 2024
- Date
- 2024-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- cervical cancer; cervigram; cervix; colposcope; Segmentation
- Coverage
- Mukku L., Computer Science and Engineering, CHRIST(Deemed to be University), Bangalore, India; Thomas J., Computer Science and Engineering, CHRIST(Deemed to be University), Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835035885-8
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Mukku L.; Thomas J., “Advanced Cervical Lesion Detection using Deep Learning Techniques,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 28, 2025, https://archives.christuniversity.in/items/show/19364.