Single-Image Multi-Parametric Representation of Optical Properties through Encodings to the HSV Color Space
The visualization of 2D clinical data often relies on color-coded images, but different colormaps can introduce cognitive biases, impacting result interpretation. Moreover, when using color for diagnosis with multiple biomarkers, the application of distinct colormaps for each parameter can hinder co...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/1/155 |
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| author | Verónica Mieites José A. Gutiérrez-Gutiérrez José M. López-Higuera Olga M. Conde |
| author_facet | Verónica Mieites José A. Gutiérrez-Gutiérrez José M. López-Higuera Olga M. Conde |
| author_sort | Verónica Mieites |
| collection | DOAJ |
| description | The visualization of 2D clinical data often relies on color-coded images, but different colormaps can introduce cognitive biases, impacting result interpretation. Moreover, when using color for diagnosis with multiple biomarkers, the application of distinct colormaps for each parameter can hinder comparisons. Our aim was to introduce a visualization technique that utilizes the hue (H), saturation (S), and value (V) in a single image to convey multi-parametric data on various optical properties in an effective manner. To achieve this, we conducted a study involving two datasets, one comprising multi-modality measurements of the human aorta and the other featuring multiple parameters of dystrophic mice muscles. Through this analysis, we determined that H is best suited to emphasize differences related to pathology, while V highlights high-spatial-resolution data disparities, and color alterations effectively indicate changes in chemical component concentrations. Furthermore, encoding structural information as S and V within the same image assists in pinpointing the specific locations of these variations. In cases where all data are of a high resolution, H remains the optimal indicator of pathology, ensuring results’ interpretability. This approach simplifies the selection of an appropriate colormap and enhances the ability to grasp a sample’s characteristics at a single glance. |
| first_indexed | 2024-03-08T15:12:25Z |
| format | Article |
| id | doaj.art-7633dd2c83144a13932416b1e1f2b2c1 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-08T15:12:25Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-7633dd2c83144a13932416b1e1f2b2c12024-01-10T14:51:08ZengMDPI AGApplied Sciences2076-34172023-12-0114115510.3390/app14010155Single-Image Multi-Parametric Representation of Optical Properties through Encodings to the HSV Color SpaceVerónica Mieites0José A. Gutiérrez-Gutiérrez1José M. López-Higuera2Olga M. Conde3Grupo de Ingeniería Fotónica, Universidad de Cantabria, Avenida Los Castros S/N, 39006 Santander, SpainGrupo de Ingeniería Fotónica, Universidad de Cantabria, Avenida Los Castros S/N, 39006 Santander, SpainGrupo de Ingeniería Fotónica, Universidad de Cantabria, Avenida Los Castros S/N, 39006 Santander, SpainGrupo de Ingeniería Fotónica, Universidad de Cantabria, Avenida Los Castros S/N, 39006 Santander, SpainThe visualization of 2D clinical data often relies on color-coded images, but different colormaps can introduce cognitive biases, impacting result interpretation. Moreover, when using color for diagnosis with multiple biomarkers, the application of distinct colormaps for each parameter can hinder comparisons. Our aim was to introduce a visualization technique that utilizes the hue (H), saturation (S), and value (V) in a single image to convey multi-parametric data on various optical properties in an effective manner. To achieve this, we conducted a study involving two datasets, one comprising multi-modality measurements of the human aorta and the other featuring multiple parameters of dystrophic mice muscles. Through this analysis, we determined that H is best suited to emphasize differences related to pathology, while V highlights high-spatial-resolution data disparities, and color alterations effectively indicate changes in chemical component concentrations. Furthermore, encoding structural information as S and V within the same image assists in pinpointing the specific locations of these variations. In cases where all data are of a high resolution, H remains the optimal indicator of pathology, ensuring results’ interpretability. This approach simplifies the selection of an appropriate colormap and enhances the ability to grasp a sample’s characteristics at a single glance.https://www.mdpi.com/2076-3417/14/1/155HSV color spaceoptical propertiesstructurechemical compositionoptical coherence tomographyhyperspectral imaging |
| spellingShingle | Verónica Mieites José A. Gutiérrez-Gutiérrez José M. López-Higuera Olga M. Conde Single-Image Multi-Parametric Representation of Optical Properties through Encodings to the HSV Color Space Applied Sciences HSV color space optical properties structure chemical composition optical coherence tomography hyperspectral imaging |
| title | Single-Image Multi-Parametric Representation of Optical Properties through Encodings to the HSV Color Space |
| title_full | Single-Image Multi-Parametric Representation of Optical Properties through Encodings to the HSV Color Space |
| title_fullStr | Single-Image Multi-Parametric Representation of Optical Properties through Encodings to the HSV Color Space |
| title_full_unstemmed | Single-Image Multi-Parametric Representation of Optical Properties through Encodings to the HSV Color Space |
| title_short | Single-Image Multi-Parametric Representation of Optical Properties through Encodings to the HSV Color Space |
| title_sort | single image multi parametric representation of optical properties through encodings to the hsv color space |
| topic | HSV color space optical properties structure chemical composition optical coherence tomography hyperspectral imaging |
| url | https://www.mdpi.com/2076-3417/14/1/155 |
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