We have made an Android application that allows a 3D thermal and geometric analysis of ulcers in the diabetic foot over time as shown in this 1 minutes video.

First, the patient is selected in the smartphone and the images of previous examinations are loaded.

Then we associate the smartphone with the FlirOne Pro thermal camera and we make thermal and colour acquisitions from several angles of view.

Then we build a 3D model both thermal and geometry.

Finally, thermal and geometric measures are captures over various examinations which allows the practitioners to follow the evolution of the ulcer from.

This easy-to-use and very fast system will be offered to be used in hospitals and medical practices to better track ulcer status in the diabetic foot. It will contribute to better care for diabetic patients.

Below you will find the scientific publications of this work. And can be download in "Database".

References

Journals

[1] Niri R., Gutierrez E., Douzi H., Lucas Y., Treuillet S.,  Castaneda B., Hernandez I., Multi-view data augmentation to improve wound segmentation on 3D surface model by deep learning, in IEEE Access, vol. 9, pp. 157628-157638, 2021 , 10.1109/ACCESS.2021.3130784 . (IF 3.367), Q1

[2] Gutierrez E., Castañeda B., Treuillet S., Hernandez I., Multimodal and Multiview Wound Monitoring with Mobile Devices. Photonics. 2021; 8(10):424. 10.3390/photonics8100424 (IF 2.676), Q2

[3] Y. Lucas, R. Niri, S. Treuillet, H. Douzi, B. Castaneda, Wound size imaging : ready for smart assessment and monitoring, Advances in Wound Care, Mary Ann Liebert publ.doi: 10.1089/wound.2018.0937. Published online 22 Apr 2020 Epub ahead of print. PMID: 32320356.

Conferences

[4] E. Gutierrez, B. Castaneda, S. Treuillet, Registration of thermal 3D models over time using low cost and portable devices, Quality Control Artificial Vision, 2023.

[5] E. Gutierrez, B. Castañeda, S. Treuillet, Y. Lucas, Combined thermal and color 3D model for wound evaluation from handheld devices SPIE Medical Imaging, 2021, 10.1117/12.2580669 .

[6] Rania Niri, Hassan Douzi, Yves Lucas and Sylvie Treuillet, A superpixel-wise fully convolutional network approach for diabetic foot ulcer tissue classification ICPR-AIHA Workshop on Artifical Intelligence for Healthcare Applications , Milano Italy 10-01- 2021

[7] E.Gutierrez, B. Castañeda, S. Treuillet, Correction of temperature estimated from a low-cost handeld infrared camera for clinical monitoring, 20th Advanced Concepts for Intelligent Vision Systems (ACIVS), Lecture Notes in Computer Sciences vol.12002: 108-116, 2020 . 10.1007/978-3-030-40605-9_10

[8] Rania Niri, Hassan Douzi, Yves Lucas and Sylvie Treuillet, Semantic segmentation of diabetic foot ulcer images : dealing with small dataset in DL approaches, LNCS 12 119, Springer, 2020

[9] Rania Niri, Hassan Douzi, Yves Lucas and Sylvie Treuillet, Semantic segmentation of diabetic foot ulcer images : dealing with small dataset in DL approaches, 9th int. ICISP conf . Marrakech, Morocco, June 4-6 2020

[10] Rania Niri, Hassan Douzi, Yves Lucas and Sylvie Treuillet, Semantic segmentation of diabetic foot ulcer images : dealing with small dataset in DL approaches Lecture Notes in Computer Science, vol 12119, Springer, Cham 10.1007/978-3-030-51935-3 17

[11] Rania Niri, Hassan Douzi, Yves Lucas and Sylvie Treuillet, Fully convolutional networks for diabetic foot ulcers diagnosis, Int. conf. on Medical Diagnostic Imaging and Radiology (ICMDIR 2020), Barcelona, Spain 05-06 march 2020

PhD Reports

[12] E.Gutierrez, Fusion of thermal and three-dimensional data for wound monitoring PhD of Orleans University France & PUCP Lima Peru 13-04-23

[13] R. Niri, 13-04-22 Deep learning for wound image analysis applied to diabetic foot ulcer, PhD of Ibn Zohr University, Agadir, Marocco