Technical Report: Automated Optical Inspection of Surgical Instruments
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arXiv
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| Autores principales: | , , |
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| Formato: | Preprint |
| Publicado: |
2026
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| _version_ | 1866908870059753472 |
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| author | Shafqat, Zunaira Jilani, Atif Aftab Ahmed Ain, Qurrat Ul |
| author_facet | Shafqat, Zunaira Jilani, Atif Aftab Ahmed Ain, Qurrat Ul |
| contents | In the dynamic landscape of modern healthcare, maintaining the highest standards in surgical instruments is critical for clinical success. This report explores the diverse realm of surgical instruments and their associated manufacturing defects, emphasizing their pivotal role in ensuring the safety of surgical procedures. With potentially fatal consequences arising from even minor defects, precision in manufacturing is paramount.The report addresses the identification and rectification of critical defects such as cracks, rust, and structural irregularities. Such scrutiny prevents substantial financial losses for manufacturers and, more crucially, safeguards patient lives. The collaboration with industry leaders Daddy D Pro and Dr. Frigz International, renowned trailblazers in the Sialkot surgical cluster, provides invaluable insights into the analysis of defects in Pakistani-made instruments. This partnership signifies a commitment to advancing automated defect detection methodologies, specifically through the integration of deep learning architectures including YOLOv8, ResNet-152, and EfficientNet-b4, thereby elevating quality standards in the manufacturing process. The scope of this report is to identify various surgical instruments manufactured in Pakistan and analyze their associated defects using a newly developed dataset of 4,414 high-resolution images. By focusing on quality assurance through Automated Optical Inspection (AOI) tools, this document serves as a resource for manufacturers, healthcare professionals, and regulatory bodies. The insights gained contribute to the enhancement of instrument standards, ensuring a more reliable healthcare environment through industry expertise and cutting-edge technology. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_05987 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Technical Report: Automated Optical Inspection of Surgical Instruments Shafqat, Zunaira Jilani, Atif Aftab Ahmed Ain, Qurrat Ul Computer Vision and Pattern Recognition Artificial Intelligence Image and Video Processing 68T07, 68T45, 68U10, 92C55 I.4.6; I.4.8; I.2.10 In the dynamic landscape of modern healthcare, maintaining the highest standards in surgical instruments is critical for clinical success. This report explores the diverse realm of surgical instruments and their associated manufacturing defects, emphasizing their pivotal role in ensuring the safety of surgical procedures. With potentially fatal consequences arising from even minor defects, precision in manufacturing is paramount.The report addresses the identification and rectification of critical defects such as cracks, rust, and structural irregularities. Such scrutiny prevents substantial financial losses for manufacturers and, more crucially, safeguards patient lives. The collaboration with industry leaders Daddy D Pro and Dr. Frigz International, renowned trailblazers in the Sialkot surgical cluster, provides invaluable insights into the analysis of defects in Pakistani-made instruments. This partnership signifies a commitment to advancing automated defect detection methodologies, specifically through the integration of deep learning architectures including YOLOv8, ResNet-152, and EfficientNet-b4, thereby elevating quality standards in the manufacturing process. The scope of this report is to identify various surgical instruments manufactured in Pakistan and analyze their associated defects using a newly developed dataset of 4,414 high-resolution images. By focusing on quality assurance through Automated Optical Inspection (AOI) tools, this document serves as a resource for manufacturers, healthcare professionals, and regulatory bodies. The insights gained contribute to the enhancement of instrument standards, ensuring a more reliable healthcare environment through industry expertise and cutting-edge technology. |
| title | Technical Report: Automated Optical Inspection of Surgical Instruments |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Image and Video Processing 68T07, 68T45, 68U10, 92C55 I.4.6; I.4.8; I.2.10 |
| url | https://arxiv.org/abs/2603.05987 |