An Efficient Edge-Based System for Nucleated Oval-Shaped Red Blood Cell Counting
The integration of innovative technologies in animal healthcare has gained significance in recent years, aiming to enhance diagnostic capabilities across various species. In this work, we address a specific challenge within avian healthcare: the accurate counting of nucleated Red Blood Cells (RBCs)....
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10794536/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841560601318391808 |
|---|---|
| author | Carlo Centofanti Daniele Lozzi Ciro Cococcetta Andrea Marotta |
| author_facet | Carlo Centofanti Daniele Lozzi Ciro Cococcetta Andrea Marotta |
| author_sort | Carlo Centofanti |
| collection | DOAJ |
| description | The integration of innovative technologies in animal healthcare has gained significance in recent years, aiming to enhance diagnostic capabilities across various species. In this work, we address a specific challenge within avian healthcare: the accurate counting of nucleated Red Blood Cells (RBCs). We propose a novel Cell Counter and Detector (CCD) algorithm, specifically designed for avian RBCs, which utilizes smartphones and optical microscopes for rapid and precise cell counting. Leveraging Multi-access Edge Computing (MEC) technology, the system ensures efficient data processing, privacy preservation, and ease of use through a user-friendly web interface. The results demonstrate that our method achieves an accuracy of 0.98, significantly outperforming existing approaches. Moreover, our system enables professionals to use the tools they already have without requiring expensive instruments. Our system leverages MEC to enable real-time processing and privacy-preserving data management, setting a new benchmark for avian blood diagnostics in terms of cost-effectiveness and accuracy. Beyond its immediate implications for avian healthcare, this research underscores the broader potential of technology in improving diagnostics for diverse animal species. |
| format | Article |
| id | doaj-art-f8d144df1d88481aa949eb2e6cc0e4d1 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-f8d144df1d88481aa949eb2e6cc0e4d12025-01-04T00:00:58ZengIEEEIEEE Access2169-35362024-01-011219562919564110.1109/ACCESS.2024.351583510794536An Efficient Edge-Based System for Nucleated Oval-Shaped Red Blood Cell CountingCarlo Centofanti0https://orcid.org/0000-0002-0903-9804Daniele Lozzi1https://orcid.org/0000-0002-6180-5131Ciro Cococcetta2https://orcid.org/0000-0003-1959-3574Andrea Marotta3https://orcid.org/0000-0003-2426-1902Department of DISIM, University of L’Aquila, L’Aquila, ItalyDepartment of DISIM, University of L’Aquila, L’Aquila, ItalyUnité NAC Centre Hospitalier Vétérinaire Saint Martin, Allonzier-la-Caille, FranceDepartment of DISIM, University of L’Aquila, L’Aquila, ItalyThe integration of innovative technologies in animal healthcare has gained significance in recent years, aiming to enhance diagnostic capabilities across various species. In this work, we address a specific challenge within avian healthcare: the accurate counting of nucleated Red Blood Cells (RBCs). We propose a novel Cell Counter and Detector (CCD) algorithm, specifically designed for avian RBCs, which utilizes smartphones and optical microscopes for rapid and precise cell counting. Leveraging Multi-access Edge Computing (MEC) technology, the system ensures efficient data processing, privacy preservation, and ease of use through a user-friendly web interface. The results demonstrate that our method achieves an accuracy of 0.98, significantly outperforming existing approaches. Moreover, our system enables professionals to use the tools they already have without requiring expensive instruments. Our system leverages MEC to enable real-time processing and privacy-preserving data management, setting a new benchmark for avian blood diagnostics in terms of cost-effectiveness and accuracy. Beyond its immediate implications for avian healthcare, this research underscores the broader potential of technology in improving diagnostics for diverse animal species.https://ieeexplore.ieee.org/document/10794536/Computer visionimage segmentationnuclei segmentationcell countingavian blood cellsmulti-access edge computing |
| spellingShingle | Carlo Centofanti Daniele Lozzi Ciro Cococcetta Andrea Marotta An Efficient Edge-Based System for Nucleated Oval-Shaped Red Blood Cell Counting IEEE Access Computer vision image segmentation nuclei segmentation cell counting avian blood cells multi-access edge computing |
| title | An Efficient Edge-Based System for Nucleated Oval-Shaped Red Blood Cell Counting |
| title_full | An Efficient Edge-Based System for Nucleated Oval-Shaped Red Blood Cell Counting |
| title_fullStr | An Efficient Edge-Based System for Nucleated Oval-Shaped Red Blood Cell Counting |
| title_full_unstemmed | An Efficient Edge-Based System for Nucleated Oval-Shaped Red Blood Cell Counting |
| title_short | An Efficient Edge-Based System for Nucleated Oval-Shaped Red Blood Cell Counting |
| title_sort | efficient edge based system for nucleated oval shaped red blood cell counting |
| topic | Computer vision image segmentation nuclei segmentation cell counting avian blood cells multi-access edge computing |
| url | https://ieeexplore.ieee.org/document/10794536/ |
| work_keys_str_mv | AT carlocentofanti anefficientedgebasedsystemfornucleatedovalshapedredbloodcellcounting AT danielelozzi anefficientedgebasedsystemfornucleatedovalshapedredbloodcellcounting AT cirocococcetta anefficientedgebasedsystemfornucleatedovalshapedredbloodcellcounting AT andreamarotta anefficientedgebasedsystemfornucleatedovalshapedredbloodcellcounting AT carlocentofanti efficientedgebasedsystemfornucleatedovalshapedredbloodcellcounting AT danielelozzi efficientedgebasedsystemfornucleatedovalshapedredbloodcellcounting AT cirocococcetta efficientedgebasedsystemfornucleatedovalshapedredbloodcellcounting AT andreamarotta efficientedgebasedsystemfornucleatedovalshapedredbloodcellcounting |