How to cite?

If you have found the database helpful please cite the following paper ''Chronic wounds multimodal image database''

BibTeX citation:

@article{KRECICHWOST2021,
title = {Chronic wounds multimodal image database},
journal = {Computerized Medical Imaging and Graphics},
volume = {88},
pages = {101844},
year = {2021},
issn = {0895-6111},
doi = {https://doi.org/10.1016/j.compmedimag.2020.101844},
url = {https://www.sciencedirect.com/science/article/pii/S0895611120301397},
author = {Michał Kręcichwost and Joanna Czajkowska and Agata Wijata and Jan Juszczyk and Bartłomiej Pyciński and Marta Biesok and Marcin Rudzki and Jakub Majewski and Jacek Kostecki and Ewa Pietka},
keywords = {Chronic wounds, Multimodal dataset, Manual outlines, Segmentation and registration, Colour photography, Thermal imaging, Depth map},
abstract = {A multimodal wound image database was created to allow fast development of computer-aided approaches for wound healing monitoring. The developed system with parallel camera optical axes enables multimodal images: photo, thermal, stereo, and depth map of the wound area to be acquired. As a result of using this system a multimodal database of chronic wound images is introduced. It contains 188 image sets of photographs, thermal images, and 3D meshes of the surfaces of chronic wounds acquired during 79 patient visits. Manual wound outlines delineated by an expert are also included in the dataset. All images of each case are additionally coregistered, and both numerical registration parameters and the transformed images are covered in the database. The presented database is publicly available for the research community at https://chronicwounddatabase.eu. That is the first publicly available database for evaluation and comparison of new image-based algorithms in the wound healing monitoring process with coregistered photographs, thermal maps, and 3D models of the wound area. Easily available database of coregistered multimodal data with the raw data set allows faster development of algorithms devoted to wound healing analysis and monitoring.}
}

RIS citation:

TY  - JOUR
T1  - Chronic wounds multimodal image database
AU  - Kręcichwost, Michał
AU  - Czajkowska, Joanna
AU  - Wijata, Agata
AU  - Juszczyk, Jan
AU  - Pyciński, Bartłomiej
AU  - Biesok, Marta
AU  - Rudzki, Marcin
AU  - Majewski, Jakub
AU  - Kostecki, Jacek
AU  - Pietka, Ewa
JO  - Computerized Medical Imaging and Graphics
VL  - 88
SP  - 101844
PY  - 2021
DA  - 2021/03/01/
SN  - 0895-6111
DO  - https://doi.org/10.1016/j.compmedimag.2020.101844
UR  - https://www.sciencedirect.com/science/article/pii/S0895611120301397
KW  - Chronic wounds
KW  - Multimodal dataset
KW  - Manual outlines
KW  - Segmentation and registration
KW  - Colour photography
KW  - Thermal imaging
KW  - Depth map
AB  - A multimodal wound image database was created to allow fast development of computer-aided approaches for wound healing monitoring. The developed system with parallel camera optical axes enables multimodal images: photo, thermal, stereo, and depth map of the wound area to be acquired. As a result of using this system a multimodal database of chronic wound images is introduced. It contains 188 image sets of photographs, thermal images, and 3D meshes of the surfaces of chronic wounds acquired during 79 patient visits. Manual wound outlines delineated by an expert are also included in the dataset. All images of each case are additionally coregistered, and both numerical registration parameters and the transformed images are covered in the database. The presented database is publicly available for the research community at https://chronicwounddatabase.eu. That is the first publicly available database for evaluation and comparison of new image-based algorithms in the wound healing monitoring process with coregistered photographs, thermal maps, and 3D models of the wound area. Easily available database of coregistered multimodal data with the raw data set allows faster development of algorithms devoted to wound healing analysis and monitoring.
ER  -

Text citation:

Michał Kręcichwost, Joanna Czajkowska, Agata Wijata, Jan Juszczyk, Bartłomiej Pyciński, Marta Biesok, Marcin Rudzki, Jakub Majewski, Jacek Kostecki, Ewa Pietka,
Chronic wounds multimodal image database,
Computerized Medical Imaging and Graphics,
Volume 88,
2021,
101844,
ISSN 0895-6111,
https://doi.org/10.1016/j.compmedimag.2020.101844.
(https://www.sciencedirect.com/science/article/pii/S0895611120301397)
Abstract: A multimodal wound image database was created to allow fast development of computer-aided approaches for wound healing monitoring. The developed system with parallel camera optical axes enables multimodal images: photo, thermal, stereo, and depth map of the wound area to be acquired. As a result of using this system a multimodal database of chronic wound images is introduced. It contains 188 image sets of photographs, thermal images, and 3D meshes of the surfaces of chronic wounds acquired during 79 patient visits. Manual wound outlines delineated by an expert are also included in the dataset. All images of each case are additionally coregistered, and both numerical registration parameters and the transformed images are covered in the database. The presented database is publicly available for the research community at https://chronicwounddatabase.eu. That is the first publicly available database for evaluation and comparison of new image-based algorithms in the wound healing monitoring process with coregistered photographs, thermal maps, and 3D models of the wound area. Easily available database of coregistered multimodal data with the raw data set allows faster development of algorithms devoted to wound healing analysis and monitoring.
Keywords: Chronic wounds; Multimodal dataset; Manual outlines; Segmentation and registration; Colour photography; Thermal imaging; Depth map