Learning-Based Vein Image Segmentation Under Variable Ambient Lighting Conditions and Sensor Noise
We present a ML-based method for binary segmentation of vein images under variant environmental lighting and sensor noise. The proposed model architecture is based on the encoder-decoder model displayed an F1 score of 0.9871 on the test set. © 2024 Satya Prasanna Mallick, Prasanth Tata, Shubham Makwana, Ram Gopal, Vandana Sharma
Authors
- Shubham Makwana
- Ram Gopal (ORCID: https://orcid.org/0000-0002-5776-9377)
- Vandana Sharma (ORCID: https://orcid.org/0000-0001-9830-2485)
- Satya Prasanna Mallick (ORCID: https://orcid.org/0000-0002-4064-6258)
- Prasanth Tata
Institutions
- Indian Institute of Technology Hyderabad (IN)
Publication Details
- Published
- 2024-08-04
- DOI
- https://doi.org/10.1109/cleo-pr60912.2024.10676479
- Primary Topic
- Photoacoustic and Ultrasonic Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00