Summary of Is Thermography a Viable Solution For Detecting Pressure Injuries in Dark Skin Patients?, by Miriam Asare-baiden et al.
Is thermography a viable solution for detecting pressure injuries in dark skin patients?
by Miriam Asare-Baiden, Kathleen Jordan, Andrew Chung, Sharon Eve Sonenblum, Joyce C. Ho
First submitted to arxiv on: 15 Nov 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a novel approach to detecting pressure injuries (PIs) using deep learning models, specifically small convolutional neural networks (CNNs). The existing methods have limitations in detecting PIs in darker skin tones and varying data collection protocols. To address this issue, the authors introduce a new dataset of 35 participants with darker skin tones, where temperature differences are induced through cooling and cupping protocols. The dataset includes different cameras, lighting, patient pose, and camera distance to simulate real-world scenarios. The performance of the CNNs trained on thermal or optical images is compared for all skin tones. Preliminary results show that thermography-based CNNs are robust to data collection protocols for all skin tones. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Pressure injuries can be difficult to detect, especially in people with darker skin tones. Researchers have been trying to find a way to use machines to help diagnose this condition. They think that taking pictures of the body using special cameras might work. The problem is that these machines don’t always do well when they’re used on people with darker skin tones. To fix this, scientists are creating a new set of pictures and videos of people with darker skin tones. These images will show what happens to their bodies when it’s cold or when pressure is applied. They’ll test special computer programs to see if they can use these images to detect pressure injuries more accurately. |
Keywords
» Artificial intelligence » Deep learning » Temperature
