Color Space Assessment for Automatic Chronic Wound Segmentation

Angela F. Palacios-Gaxiola, Stewart R. Santos-Arce, Senior Member, IEEE Sulema Torres-Ramos, Israel Román-Godínez, Ricardo A. Salido-Ruiz

📄 Article

Cargando artículo…

🖼️ Poster

Cargando póster…

📚 References

  1. B. Cassidy et al., "An Enhanced Harmonic Densely Connected Hybrid Transformer Network Architecture for Chronic Wound Segmentation Utilizing Multi-Colour Space Tensor Merging," Comput Biol Med, vol. 192, p. 110172, Oct. 2024.
  2. D. Marijanović and D. Filko, "A Systematic Overview of Recent Methods for Non-Contact Chronic Wound Analysis," Applied Sciences, vol. 10, no. 21, p. 7613, Oct. 2020.
  3. S. N. Gowda y C. Yuan, "ColorNet: Investigating the Importance of Color Spaces for Image Classification," in Lecture Notes in Computer Science, 2019.
  4. M. Kręcichwost et al., "Chronic wounds multimodal image database," Computerized Medical Imaging and Graphics, vol. 88, p. 101844, 2021.
  5. G. Jocher y J. Qiu, Ultralytics YOLO11, version 11.0.0, 2024. [Online]. Available: GitHub
  6. P. Iakubovskii, Segmentation Models, GitHub repository, 2019. [Online]. Available: GitHub