A Tool for Thermal Image Annotation and Automatic Temperature Extraction around Orthopedic Pin Sites

Annadatha, Sowmya; Fridberg, Marie; Kold, Søren; Rahbek, Ole; Shen, Ming

doi:10.1109/ipas55744.2022.10053084

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…The choice of tool often depends on personal preference, project requirements, and the specific desired features. Commonly used tools include Visual Object Tagging Tool (VoTT) [73], VGG Image Annotator (VIA) [74], and Roboflow [75] which is a popular platform for managing, preprocessing, and annotating datasets for computer vision tasks. It provides a comprehensive end-to-end solution for dataset management, annotation, and preprocessing, offering a range of features that can help streamline your object detection workflow.…”

Section: Confidence(p) = Probability(p) × Iou (Prediction Target)mentioning

confidence: 99%

A Comprehensive Systematic Review of YOLO for Medical Object Detection (2018 to 2023)

Ragab,

Abdulkadir,

Muneer

et al. 2024

IEEE Access

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Under the grant projects ''015LC0-308 for YUTP-FRG'' and ''015MA0-158 for FRGS'' ABSTRACT YOLO (You Only Look Once) is an extensively utilized object detection algorithm that has found applications in various medical object detection tasks. This has been accompanied by the emergence of numerous novel variants in recent years, such as YOLOv7 and YOLOv8. This study encompasses a systematic exploration of the PubMed database to identify peer-reviewed articles published between 2018 and 2023. The search procedure found 124 relevant studies that employed YOLO for diverse tasks including lesion detection, skin lesion classification, retinal abnormality identification, cardiac abnormality detection, brain tumor segmentation, and personal protective equipment detection. The findings demonstrated the effectiveness of YOLO in outperforming alternative existing methods for these tasks. However, the review also unveiled certain limitations, such as well-balanced and annotated datasets, and the high computational demands. To conclude, the review highlights the identified research gaps and proposes future directions for leveraging the potential of YOLO for medical object detection.

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Section: Confidence(p) = Probability(p) × Iou (Prediction Target)mentioning

confidence: 99%

A Comprehensive Systematic Review of YOLO for Medical Object Detection (2018 to 2023)

Ragab,

Abdulkadir,

Muneer

et al. 2024

IEEE Access

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Can pin-site inflammation be detected with thermographic imaging? A cross-sectional study from the USA and Denmark of patients treated with external fixators

Fridberg,

Rahbek,

Husum

et al. 2024

ActaO

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Background and purpose: Patients with external fixators are at risk of pin-site infection. A tool for objective monitoring of pin sites for evolving signs of infection is warranted. We aimed to investigate the temperature (MaxTp) difference between clean and visually inflamed pin sites using thermography and to establish the optimal cut-off value of MaxTp using thermography as a screening tool for inflammation detection.Methods: This was a cross-sectional study performed in the USA and Denmark of patients with circular external fixators. Pin sites were visually judged by a surgeon or a nurse as clean or as showing signs of inflammation. The MaxTp was obtained at the pin site by thermographic imaging using an infrared camera (FLIR T540).Results: We included 1,970 pin sites from 83 patients. The mean MaxTp for clean pin sites (n = 1,739) was 33.1°C (95% confidence interval [CI] 32.8–33.4) and the mean MaxTp for visual inflamed pin sites (n = 231) was 34.0°C (CI 33.6–34.3). The mean difference, when adjusted for repeated observations of patients and pin sites, was statistically significant with a difference of 0.9°C (CI 0.7–1.1) (P < 0.001). The area under the receiver operating characteristic curve for MaxTp as a screening tool to detect visual signs of inflammation was 0.71 (CI 0.65–0.76). The empirically optimal cut-off value was 34.1°C with a sensitivity of 65%, a specificity of 72%, a positive predictive value of 23%, and a negative predictive value of 94%.Conclusion: We found a statistically significant difference in mean temperature between pin sites with and without visual signs of inflammation. Thermography could be a promising tool for future point of care technology for monitoring inflammation around pin sites.

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A Tool for Thermal Image Annotation and Automatic Temperature Extraction around Orthopedic Pin Sites

Cited by 2 publications

References 13 publications

A Comprehensive Systematic Review of YOLO for Medical Object Detection (2018 to 2023)

A Comprehensive Systematic Review of YOLO for Medical Object Detection (2018 to 2023)

Can pin-site inflammation be detected with thermographic imaging? A cross-sectional study from the USA and Denmark of patients treated with external fixators

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