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Hair transplant assessment in Asian men with receding hairlines using images and computer vision techniques

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Abstract

This study addresses the current challenges in obtaining preliminary cost estimates for hair transplant procedures, which often involve time-consuming and frustrating communication between clinics and patients. Our goal is to streamline this process by integrating image processing and computer visualization techniques into an application tailored for individuals seeking hair transplantation services. Specifically, our focus is on Asian men experiencing hair loss in Stages 1 to 3. To achieve this, we have developed an image acquisition app, enhanced images as necessary using GFP-GAN, and performed image segmentation with BiSeNet. Additionally, we utilized MediaPipe to create new hairline projections for individuals with receding hairlines. This comprehensive approach allows us to calculate the hair recipient area and the required number of hair grafts accurately. Comparing our estimations to actual measurements, our method shows errors ranging from -15% to +25%, whereas estimations provided by hair clinics range from -35% to +18%. This highlights the superior accuracy of our individual-specific estimations compared to the general guidelines found on internet sources, enabling a more precise cost estimate for patients.

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Data availability

All measurements used in calculation were collected by the authors. The computer specifications used in this study are provided in the Appendix. All codes used in the study are written in Python, specifically Version 3.10.11. The libraries used include: NumPy version 1.25.0; OpenCV version 4.7.0; MediaPipe version 0.9.3.0; Matplotlib version 3.4.3; Plotly version 5.14.1; Open3D version 0.17.0; Scipy version 1.10.1; PyTorch version 2.0.1; Torchvision version 0.15.2 + cpu. The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

Special thanks to Mr. Vatchara R. and Mr. Tawatchai S. for serving as our models, allowing us to collect measurements.

Funding

No funds, grants, or other support was received for conducting this study.

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Authors and Affiliations

  1. Graduate School of Applied Statistics, National Institute of Development Administration, 148 SeriThai Road, Klong-Chan, Bangkapi, Bangkok, 10240, Thailand

    Sorawit Sinlapanurak, Korawee Peerasantikul, Napat Phongvichian, Kruawun Jankaew, Pimchayanan Kusontramas & Thitirat Siriborvornratanakul

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  1. Sorawit Sinlapanurak
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  2. Korawee Peerasantikul
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  3. Napat Phongvichian
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All authors contributed equally.

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Correspondence to Thitirat Siriborvornratanakul.

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Appendix: Computer specifications

Appendix: Computer specifications

  1. (1)

    Processor: Intel(R) Core(TM) i5-8300H CPU @ 2.30 GHz, GPU Device name: NVIDIA GeForce GTX 1050; RAM: 24 GB; Disk: 500 GB; OS: Windows 11 Home Single Language.

  2. (2)

    Processor: AMD Ryzen 7 5800H with Radeon Graphics 3.20 GHz.; GPU Device name: NVIDIA GeForce RTX 3070 8 GB, RAM: 32 GB, Disk: 1 TB; OS: Windows 11 Home Single Language

  3. (3)

    Processor: AMD Ryzen 7 3700X 8-Core Processor 3.60 GHz; GPU Device name: AMD Radeon RX5700XT 8 GB; RAM: 16 GB; Disk: 1 TB; OS: Windows 11 Home

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Sinlapanurak, S., Peerasantikul, K., Phongvichian, N. et al. Hair transplant assessment in Asian men with receding hairlines using images and computer vision techniques. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-18619-9

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  • DOI: https://doi.org/10.1007/s11042-024-18619-9

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