Automated detection of posterior urethral valves in voiding cystourethrography images: A novel AI-Based pipeline for enhanced diagnosis and classification
PUV detection from VCUG images through automated segmentation and processing can reduce subjectivity and decrease physician workloads. The proposed approach can serve as a foundation for future efforts to fully automate PUV diagnosis and follow-up.
Authors
- Tariq O. Abbas (ORCID: https://orcid.org/0000-0002-8425-4029)
- Anil Takvani (ORCID: https://orcid.org/0009-0001-4283-5802)
- Mansour Ali
- Muhammad E. H. Chowdhury (ORCID: https://orcid.org/0000-0003-0744-8206)
- Saidul Kabir (ORCID: https://orcid.org/0000-0002-6102-3180)
- Rusab Sarmun (ORCID: https://orcid.org/0009-0004-4887-0627)
- Elias Ramírez-Velázquez
Institutions
- Qatar Airways (Qatar) (QA)
- University of Dhaka (BD)
- Hospital Infantil de México Federico Gómez (MX)
- Weill Cornell Medical College in Qatar (QA)
- Qatar University (QA)
Publication Details
- Journal
- Computers in Biology and Medicine
- Published
- 2024-12-19
- DOI
- https://doi.org/10.1016/j.compbiomed.2024.109509
- Citations
- 4
- Primary Topic
- Pediatric Urology and Nephrology Studies
- Type
- article
- Field-Weighted Citation Impact
- 4.44
Funders
- Hamad Medical Corporation
- Sidra Medicine