Chronic wounds are a major healthcare problem worldwide which mainly a ects geriatric
population and patients with limited mobility. In tropical countries, Cutaneous Leishmaniasis
(CL) is also a cause for chronic wounds, being endemic in 75% of Peru . In this context,
the assessment of these type of wounds represents a big challenge due to the limited access
to specialized medical resources.
This work aims to develop a video-based method to compute the 3D point cloud of skin
wounds which could provide accurate metrics for medical assessment despite of the location
of the patient. Recently, CL specialists have used metrics as volume in clinical assessment
with promising results.
The acquisition protocol is prompt to be user friendly and feasible in remote locations;
the video is taken using a commercial hand-held video camera without a rig or special
illumination. The algorithm follows the Structure from Motion methodology: FAST feature
detector, pyramidal optical flow and Jacob’s method for missing points estimation.
The results show good performance in terms of accuracy and repeatability of the point
cloud computation, less than 0.6 mm and 0.21 mm respectively. However, experiments
suggest that the volume computation technique does not adapt well to the proposed method
output and requires a deeper analysis.
The method has been entirely implemented using open source libraries. / Tesis
| Identifer | oai:union.ndltd.org:PUCP/oai:tesis.pucp.edu.pe:20.500.12404/8135 |
| Date | 09 March 2017 |
| Creators | Casas Guido, Eda Leslie Mónica |
| Contributors | Castañeda Aphan, Benjamín |
| Publisher | Pontificia Universidad Católica del Perú, PE |
| Source Sets | Pontificia Universidad Católica del Perú |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/masterThesis |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/closedAccess |
Page generated in 0.0021 seconds