Article
Open Access
Automated Image-Based Detection and Measurement of Wheal Responses in Skin Prick Test Images
Zeenal Punamiya
1
,
Shravani Desai
1
,
Shravani Desai
1
1
Medical Innovation Creativity and Entrepreneurship (M.I.C.E) Lab, Grant Government Medical College and Sir J.J. Group of Hospitals, 6th Floor, New Administration Building, J.J. Hospital Campus, Byculla, Mumbai 400008, India
Journal
Impact in Computics
Volume
2
Article Number
6
Pages
1–11
Received
17 July 2026
Revised
2 September 2026
Accepted
3 September 2026
Published
9 September 2026
Views
17
Downloads
7
Abstract
Allergic disorders are common conditions caused by immune responses to otherwise harmless substances. The Skin Prick Test (SPT) is commonly employed to evaluate sensitivity to particular allergens, with the development of wheals acting as a significant visible reaction. However, manual identification and measurement of wheal size from SPT images may introduce observer variability. This study presents an automated image-analysis system for detecting and quantitatively measuring wheal responses in SPT images. The system was developed using Streamlit, OpenCV, and Imutils for image preprocessing, colour segmentation, contour detection, reference-based calibration, and wheal measurement. On the 30-image held-out evaluation subset, the mean absolute error between the automated measurements and the available reference measurements was 0.48 ± 0.12 mm. The previously reported detection accuracy and false positive/false negative rates could not be maintained as the source dataset lacked sufficient per-wheal ground truth to reconstruct the TP, FP, FN and TN counts independently. The system is computationally lightweight and operates through a standard web interface without specialized hardware. These findings support the feasibility of automated wheal detection and measurement as a computer-assisted approach to SPT image analysis. The system does not independently diagnose allergy or identify the causative allergen and further validation using independently annotated clinical datasets is required.
Keywords
skin prick test
image processing
computer vision
streamlit
wheal detection
automated measurement
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