Name
Abstract | ||
|---|---|---|
Current medical practice for determining hemoglobin concentration (which is especially important for anemic patients in need of blood transfusion) involves frequent blood tests. In this work, we propose an alternative, non-invasive approach to hemoglobin estimation, based on image analysis of a specific conjunctival region. Our ultimate goal is to develop an easy-to-use wearable device that patients themselves can employ at home to autonomously assess their need of blood transfusion. In this paper, we detail the prototype of our device and the methodology for extracting key information from the color values of the acquired image. Tests conducted on 77 anemic and healthy patients show significant correlation between the real hemoglobin value obtained through blood sampling and the value estimated by our algorithm. A prototypical binary classification algorithm for assessing the need of blood transfusion yielded good results in terms of accuracy, specificity and sensitivity, thus making it possible to avoid a significant number of blood tests. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/MeMeA.2016.7533760 | 2016 IEEE International Symposium on Medical Measurements and Applications (MeMeA) |
Keywords | Field | DocType |
hemoglobin,conjunctiva,non-invasive,computer vision | Computer vision,Binary classification,Wearable computer,Blood transfusion,Image segmentation,Artificial intelligence,Blood sampling,Medicine | Conference |
ISBN | Citations | PageRank |
978-1-4673-9173-3 | 2 | 0.51 |
References | Authors | |
2 | 11 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vitoantonio Bevilacqua | 1 | 468 | 66.40 |
| Giovanni Dimauro | 2 | 4 | 1.02 |
| Francescomaria Marino | 3 | 68 | 8.96 |
| Antonio Brunetti | 4 | 6 | 2.95 |
| Fabio Cassano | 5 | 2 | 0.51 |
| Antonio Di Maio | 6 | 4 | 1.57 |
| Enrico Nasca | 7 | 2 | 0.85 |
| Gianpaolo Francesco Trotta | 8 | 3 | 1.19 |
| Francesco Girardi | 9 | 6 | 2.70 |
| Angelo Ostuni | 10 | 2 | 0.51 |
| Attilio Guarini | 11 | 6 | 1.34 |