Emmanuel Karlo Nyarko

About

Emmanuel Karlo Nyarko is a pioneering researcher at the intersection of computer vision, robotics, and medical technology, with a primary focus on leveraging RGB-D sensors for healthcare applications. His most significant contributions lie in developing automated systems for chronic wound assessment, where he has created innovative methods for wound detection, 3D reconstruction, segmentation, and measurement using affordable depth-sensing cameras like the Microsoft Kinect. His landmark 2018 paper on fruit recognition via convex surface detection in RGB-D images has garnered 54 citations, demonstrating his broader expertise in object recognition. Nyarko’s work on wound measurement and reconstruction, including his 2016 and 2021 studies on Kinect v2-based systems and robot-driven 3D reconstruction, has accumulated over 100 citations collectively, reflecting substantial impact in the medical imaging community. He has also contributed to mobile robot localization using 3D planar surface segments, showcasing versatility in robotics. Notably, his recent 2022 and 2023 papers integrate simple feedforward neural networks and robot-driven systems to enhance wound analysis accuracy, addressing the global burden of chronic wounds exacerbated by aging populations and diabetes. Nyarko’s research bridges affordable sensor technology with clinical needs, offering practical, scalable solutions for wound care.

Research Focus

Key Achievements

Top Papers

1. 1
   A nearest neighbor approach for fruit recognition in RGB-D images based on detection of convex surfaces

   54 citations · 2018
2. 2
   Wound measurement by RGB-D camera

   24 citations · 2018
3. 3
   Detection, Reconstruction and Segmentation of Chronic Wounds Using Kinect v2 Sensor

   16 citations · 2016
4. 4
   Automatic Robot-Driven 3D Reconstruction System for Chronic Wounds

   16 citations · 2021
5. 5
   Wound Detection by Simple Feedforward Neural Network

   13 citations · 2022
6. 6
   2D/3D Wound Segmentation and Measurement Based on a Robot-Driven Reconstruction System

   11 citations · 2023
7. 7
   Wound detection and reconstruction using RGB-D camera

   8 citations · 2016
8. 8
   Fast Pose Tracking Based on Ranked 3D Planar Patch Correspondences

   7 citations · 2012
9. 9
   Global Localization Based on 3D Planar Surface Segments Detected by a 3D Camera

   6 citations · 2014
10. 10
    Global Localization Based on 3D Planar Surface Segments

    6 citations · 2013

Key Collaborators

Contact & Links