Narrative review: Diabetic foot and infrared thermography

Hernandez-Contreras, D.; Peregrina-Barreto, Hayde; Rangel-Magdaleno, José; Gonzalez, Jesús A.

doi:10.1016/j.infrared.2016.07.013

Cited by 83 publications

(66 citation statements)

References 75 publications

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“…Harding et al [22] performed a study to assess the infra-red imaging for the prevention of secondary osteomyelitis. Similarly, infrared thermography has been used in various studies to detect the complications related to the DFU [23], [24].…”

Section: Introductionmentioning

confidence: 99%

Robust Methods for Real-Time Diabetic Foot Ulcer Detection and Localization on Mobile Devices

Goyal¹,

Reeves²,

Rajbhandari³

et al. 2019

IEEE J. Biomed. Health Inform.

159

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Current practice for Diabetic Foot Ulcers (DFU) screening involves detection and localization by podiatrists. Existing automated solutions either focus on segmentation or classification. In this work, we design deep learning methods for real-time DFU localization. To produce a robust deep learning model, we collected an extensive database of 1775 images of DFU. Two medical experts produced the ground truths of this dataset by outlining the region of interest of DFU with an annotator software. Using 5-fold cross-validation, overall, Faster R-CNN with InceptionV2 model using two-tier transfer learning achieved a mean average precision of 91.8%, the speed of 48 ms for inferencing a single image and with a model size of 57.2 MB. To demonstrate the robustness and practicality of our solution to real-time prediction, we evaluated the performance of the models on a NVIDIA Jetson TX2 and a smartphone app. This work demonstrates the capability of deep learning in real-time localization of DFU, which can be further improved with a more extensive dataset.

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Section: Introductionmentioning

confidence: 99%

Robust Methods for Real-Time Diabetic Foot Ulcer Detection and Localization on Mobile Devices

Goyal¹,

Reeves²,

Rajbhandari³

et al. 2019

IEEE J. Biomed. Health Inform.

159

View full text Add to dashboard Cite

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“…Specifically, the detection of anomalies in dermal thermometry, such as diabetic foot assessment, is commonly based on a contralateral limb's temperature analysis. This procedure compares the temperature between both limbs and considers a threshold in temperature variation larger than 2.2 • C as a warning sign [17,24,28,50].…”

Section: Discussionmentioning

confidence: 99%

Performance Assessment of Low-Cost Thermal Cameras for Medical Applications

Villa

Arteaga-Marrero

Ruiz-Alzola

2020

Sensors

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Thermal imaging is a promising technology in the medical field. Recent developments in low-cost infrared (IR) sensors, compatible with smartphones, provide competitive advantages for home-monitoring applications. However, these sensors present reduced capabilities compared to more expensive high-end devices. In this work, the characterization of thermal cameras is described and carried out. This characterization includes non-uniformity (NU) effects and correction as well as the thermal cameras’ dependence on room temperature, noise-equivalent temperature difference (NETD), and response curve stability with temperature. Results show that low-cost thermal cameras offer good performance, especially when used in temperature-controlled environments, providing evidence of the suitability of such sensors for medical applications, particularly in the assessment of diabetic foot ulcers on which we focused this study.

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“…Gatt et al [24] demonstrate that the probability of complications of PAD, neuropathy, and/or neuroischaemia being present increases as the temperature of these regions rises. A narrative review on the various techniques used for diabetic foot complications based on asymmetry analysis, stress test and temperature distribution analysis is given by Hernandez-Contreras et al [25].…”

Section: Literature Review On Diabetic Foot Complications Assessment mentioning

confidence: 99%