Atef A, El-Rashidy MA, Azeem AA, Kabel AM. The role of stem cell factor in hyperpigmented skin lesions. Asian Pacific J Cancer Prev: APJCP. 2019;20(12):3723.
Troyanova P, Borisova E, Avramov L. Fluorescence and reflectance properties of hemoglobin-pigmented skin disorders. In: International Conference on Lasers, Applications, and Technologies 2007: Laser Technologies for Medicine. vol. 6734. SPIE; 2007. pp. 142–149.
Gong H, Desvignes M. Hemoglobin and melanin quantification on skin images. In: Image Analysis and Recognition: 9th International Conference, ICIAR 2012, Aveiro, Portugal, June 25-27, 2012. Proceedings, Part II 9. Springer; 2012. pp. 198–205.
Goldsberry A, Hanke CW, Hanke KE. VISIA system: a possible tool in the cosmetic practice. J Drugs Dermatol: JDD. 2014;13(11):1312–4.
Linming F, Wei H, Anqi L, Yuanyu C, Heng X, Sushmita P, et al. Comparison of two skin imaging analysis instruments: the VISIA from Canfield vs. the ANTERA 3D CS from Miravex. Skin Res Technol. 2018;24(1):3–8.
Dobrev H. Fluorescence diagnostic imaging in patients with acne. Photodermatol, Photoimmunol Photomed. 2010;26(6):285–9.
Zonios G, Bykowski J, Kollias N. Skin melanin, hemoglobin, and light scattering properties can be quantitatively assessed in vivo using diffuse reflectance spectroscopy. J Invest Dermatol. 2001;117(6):1452–7.
Jung B, Choi B, Durkin AJ, Kelly KM, Nelson JS. Characterization of port wine stain skin erythema and melanin content using cross-polarized diffuse reflectance imaging. Lasers Surg Med. 2004;34(2):174–81.
Kojima K, Shido K, Tamiya G, Yamasaki K, Kinoshita K, Aiba S. Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks. Sci Rep. 2021;11(1):1213.
Tsumura N, Ojima N, Sato K, Shiraishi M, Shimizu H, Nabeshima H, et al. Image-based skin color and texture analysis/synthesis by extracting hemoglobin and melanin information in the skin. In: ACM SIGGRAPH 2003 Papers. Association for Computing Machinery; 2003. pp. 770–779.
Jakovels D, Spigulis J, Saknite I. Multi-spectral mapping of in vivo skin hemoglobin and melanin. In: Biophotonics: Photonic Solutions for Better Health Care II. vol. 7715. SPIE; 2010. pp. 575–580.
Demirli R, Otto P, Viswanathan R, Patwardhan S, Larkey J. RBX® technology overview. Canfield Syst White Pap. 2007;1:1–5.
Tsumura N, Haneishi H, Miyake Y. Independent-component analysis of skin color image. JOSA A. 1999;16(9):2169–76.
Liu Y, Jain A, Eng C, Way DH, Lee K, Bui P, et al. A deep learning system for differential diagnosis of skin diseases. Nat Med. 2020;26(6):900–8.
Kaymak R, Kaymak C, Ucar A. Skin lesion segmentation using fully convolutional networks: a comparative experimental study. Expert Syst Appl. 2020;161: 113742.
Jha D, Smedsrud PH, Riegler MA, Johansen D, De Lange T, Halvorsen P. Resunet++: An advanced architecture for medical image segmentation. In: IEEE International Symposium on Multimedia (ISM). IEEE; 2019. pp. 225–2255.
Singh NK, Raza K. Medical image generation using generative adversarial networks: A review. Health informatics: A computational perspective in healthcare; 2021. pp. 77–96.
Tripathy S, Kannala J, Rahtu E. Learning image-to-image translation using paired and unpaired training samples. In: Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth, Australia, December 2–6, 2018, Revised Selected Papers, Part II 14. Springer; 2019. pp. 51–66.
Isola P, Zhu JY, Zhou T, Efros AA. Image-to-image translation with conditional adversarial networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition. IEEE; 2017. pp. 1125–1134.
Zhu JY, Park T, Isola P, Efros AA. Unpaired image-to-image translation using cycle-consistent adversarial networks. In: Proceedings of the IEEE international conference on computer vision. IEEE; 2017. pp. 2223–2232.
Wang TC, Liu MY, Zhu JY, Tao A, Kautz J, Catanzaro B. High-resolution image synthesis and semantic manipulation with conditional gans. In: Proceedings of the IEEE conference on computer vision and pattern recognition. IEEE; 2018. pp. 8798–8807.
Chen Q, Koltun V. Photographic image synthesis with cascaded refinement networks. In: Proceedings of the IEEE international conference on computer vision. IEEE; 2017. pp. 1511–1520.
Jung G, Lee J, Kim S. Spectrum-based deep learning framework for dermatological pigment analysis and simulation. Comput Biol Med. 2024;178: 108741. https://doi.org/10.1016/j.compbiomed.2024.108741.
Jung G, Kim S, Lee J, Yoo S. Deep learning-based optical approach for skin analysis of melanin and hemoglobin distribution. J Biomed Optics. 2023;28(3): 035001.
Jung G, Kim S, Lee J, Yoo S. Deep learning-based pigment analysis model trained with optical approach and ground truth assistance. J Biophotonics. 2023;16(12): e202300231.
Jung G, Kim S, Lee J, Yoo S. Generation of skin tone and pigmented region-modified images using a pigment discrimination model trained with an optical approach. Skin Res Technol. 2023;29(10): e13486.
Alotaibi S, Smith W. Biofacenet: Deep biophysical face image interpretation. arXiv preprint arXiv:1908.10578. 2019.
Xu C, Wang J, Yang W, Yu L. Dot distance for tiny object detection in aerial images. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE; 2021. pp. 1192–1201.
Buslaev A, Iglovikov VI, Khvedchenya E, Parinov A, Druzhinin M, Kalinin AA. Albumentations: fast and flexible image augmentations. Information. 2020;11(2):125.
Dolotov L, Sinichkin YP, Tuchin V, Utz S, Altshuler G, Yaroslavsky I. Design and evaluation of a novel portable erythema-melanin-meter. Lasers Surg Med. 2004;34(2):127–35.
Setiadi DRIM. PSNR vs. SSIM: imperceptibility quality assessment for image steganography. Multimedia Tools Appl. 2021;80(6):8423–44.
Jiang J, Liu D, Gu J, Süsstrunk S. What is the space of spectral sensitivity functions for digital color cameras? In: IEEE Workshop on Applications of Computer Vision (WACV). IEEE; 2013, pp. 168–79.
Puth MT, Neuhäuser M, Ruxton GD. Effective use of Pearson’s product-moment correlation coefficient. Anim Behav. 2014;93:183–9.
Lee CC, Wu HC, Tsai CS, Chu YP. Adaptive lossless steganographic scheme with centralized difference expansion. Pattern Recogn. 2008;41(6):2097–106.
Borji A. Pros and cons of GAN evaluation measures: new developments. Comput Vis Image Underst. 2022;215: 103329.
Chanda T, Hauser K, Hobelsberger S, Bucher TC, Garcia CN, Wies C, et al. Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma. Nat Commun. 2024;15(1):524.
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