Damir Filko
Papers
13
Total Citations
120
H-Index
7
About
Damir Filko’s research sits at the intersection of computer vision, robotics, and medical technology, with a primary focus on automated wound assessment. His pioneering work leverages inexpensive RGB-D sensors—originally developed for gaming—to create practical, low-cost systems for chronic wound detection, 3D reconstruction, and measurement. Filko’s most cited paper, “Wound Measurement by RGB-D Camera” (2018, 24 citations), established a foundation for non-contact wound analysis. He further advanced the field by integrating neural networks for wound detection and developing robot-driven reconstruction systems that automate the entire assessment pipeline, as seen in his 2021 and 2023 works (16 and 11 citations, respectively). Beyond wound care, Filko has contributed to mobile robot localization using 3D planar surface segments and low-cost robot arm positioning with visual guidance. His work addresses a critical global health challenge—chronic wounds exacerbated by aging populations and rising diabetes rates—by offering scalable, accessible solutions that reduce the burden on medical facilities. With over 100 combined citations, Filko’s research demonstrates how affordable sensor technology and intelligent algorithms can bring sophisticated medical diagnostics to wider clinical use.
Research Focus
Key Achievements
Top Papers
- 1Wound measurement by RGB-D camera24 citations · 2018
- 2
- 3Automatic Robot-Driven 3D Reconstruction System for Chronic Wounds16 citations · 2021
- 4Wound Detection by Simple Feedforward Neural Network13 citations · 2022
- 5
- 6Wound detection and reconstruction using RGB-D camera8 citations · 2016
- 7Fast Pose Tracking Based on Ranked 3D Planar Patch Correspondences7 citations · 2012
- 8Low cost robot arm with visual guided positioning7 citations · 2017
- 9
- 10Global Localization Based on 3D Planar Surface Segments6 citations · 2013