Standard Procedures for Infrared Imaging in Medicine

Ammer, K.; Ring, Francis

doi:10.1201/9781420008340.ch22

Cited by 27 publications

(36 citation statements)

References 14 publications

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“…Where appropriate, any measurement site with exposed hair was shaved at least 36 h before testing (Togawa and Saito, 1994) to prevent inflammation or damage to the skin surface artificially raising skin temperature and influencing infrared measurements (Merla et al, 2010). In preparation for testing, participants did not engage in exercise, ingest caffeine or alcohol 24 h prior to (Ammer and Ring, 2006), have a hot shower within two hours of arriving to the laboratory and kept the measurement sites clean of ointments and cosmetics (Selfe et al, 2006).…”

Section: Pre-experimental Protocolmentioning

confidence: 99%

“…Data collection consisted of repeated skin temperature measurements taken using a calibrated, uncooled digital infrared camera A305sc (FLIR Systems, Wilsonville, Oregon, USA) with an image resolution of 320 Â 240 pixels and a minimal detectable temperature difference of o 0.05°C at 30°C. The infrared camera was positioned on a level tripod perpendicular to the seated, resting participant (90°) at a distance of 0.8-1.1 m depending on the height and size of the participant (Ammer and Ring, 2006). The camera was assembled and allowed to stabilise for at least 60 min prior to subject arrival (Grgić and Pušnik, 2011).…”

Section: Experimental Protocolmentioning

confidence: 99%

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The effect of using different regions of interest on local and mean skin temperature

Maniar

Bach

Stewart

et al. 2015

Journal of Thermal Biology

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The dynamic nature of tissue temperature and the subcutaneous properties, such as blood flow, fatness, and metabolic rate, leads to variation in local skin temperature. Therefore, we investigated the effects of using multiple regions of interest when calculating weighted mean skin temperature from four local sites. Twenty-six healthy males completed a single trial in a thermonetural laboratory (mean ± SD): 24.0 (1.2)°C; 56 (8%) relative humidity; <0.1 m/s air speed). Mean skin temperature was calculated from four local sites (neck, scapula, hand and shin) in accordance with International Standards using digital infrared thermography. A 50 mm × 50 mm, defined by strips of aluminium tape, created six unique regions of interest, top left quadrant, top right quadrant, bottom left quadrant, bottom right quadrant, centre quadrant and the entire region of interest, at each of the local sites. The largest potential error in weighted mean skin temperature was calculated using a combination of a) the coolest and b) the warmest regions of interest at each of the local sites. Significant differences between the six regions interest were observed at the neck (P<0.01), scapula (P<0.001) and shin (P<0.05); but not at the hand (P = 0.482). The largest difference (± SEM) at each site was as follows: neck 0.2 (0.1)°C; scapula 0.2 (0.0)°C; shin 0.1 (0.0)°C and hand 0.1 (0.1)°C. The largest potential error (mean ± SD) in weighted mean skin temperature was 0.4 (0.1)°C (P<0.001) and the associated 95% limits of agreement for these differences was 0.2-0.5 °C. Although we observed differences in local and mean skin temperature based on the region of interest employed, these differences were minimal and are not considered physiologically meaningful.

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Section: Pre-experimental Protocolmentioning

confidence: 99%

Section: Experimental Protocolmentioning

confidence: 99%

The effect of using different regions of interest on local and mean skin temperature

Maniar

Bach

Stewart

et al. 2015

Journal of Thermal Biology

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“…The room has an ambient temperature of 20 • C and a relative humidity of 50%. Avoidance of air currents on hand subjects and shunning of direct sunlight on the lens are necessary [15]. Additionally, the distance between the infrared camera and the subject's hand is considered.…”

Section: Protocol For Acquisition Of Infrared Imagesmentioning

confidence: 99%

Spatial-temporal features of thermal images for Carpal Tunnel Syndrome detection

Roldan

Piedrahita

Benítez

2014

Image Processing: Algorithms and Systems XII

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Disorders associated with repeated trauma account for about 60% of all occupational illnesses, Carpal Tunnel Syndrome (CTS) being the most consulted today. Infrared Thermography (IT) has come to play an important role in the field of medicine. IT is non-invasive and detects diseases based on measuring temperature variations. IT represents a possible alternative to prevalent methods for diagnosis of CTS (i.e. nerve conduction studies and electromiography). This work presents a set of spatial-temporal features extracted from thermal images taken in healthy and ill patients. Support Vector Machine (SVM) classifiers test this feature space with Leave One Out (LOO) validation error. The results of the proposed approach show linear separability and lower validation errors when compared to features used in previous works that do not account for temperature spatial variability.

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“…Avoidance of air currents on hands subjects and shunning of direct sunlight on lens are necessary [11]. Additionally, the distance between the infrared camera and the subject's hand is considered.…”

Section: B Protocol For Acquisition Of Infrared Imagesmentioning

confidence: 99%

“…The proper position of the subject is important, to ensure that the collection of infrared images remain standardized and avoid uncertainties in the measurements [11].…”

Section: B Protocol For Acquisition Of Infrared Imagesmentioning

confidence: 99%

Design and implementation of a protocol for acquisition and processing of infrared images obtained from hands

Roldan

Piedrahita

Benítez

2013

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013

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Disorders associated with repeated trauma account for about 60% of all occupational illnesses, being Carpal Tunnel Syndrome (CTS), the most consulted today. Infrared Thermography (IT) has come to play an important role in the field of medicine, where diseases are detected by temperature variations. In this paper we present the extraction of temperature variations in space and time from hands of healthy and ill subjects with CTS. These features are expected to give support to the analysis of CTS using IT. The paper presents a theoretical framework of CTS, a protocol to acquire infrared images and create a standardized collection. The techniques used for image registration and feature extraction are included. Finally, the results obtained with representative features in images of healthy subjects are presented and compared against features extracted from patientss with CTS.

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Standard Procedures for Infrared Imaging in Medicine

Cited by 27 publications

References 14 publications

The effect of using different regions of interest on local and mean skin temperature

The effect of using different regions of interest on local and mean skin temperature

Spatial-temporal features of thermal images for Carpal Tunnel Syndrome detection

Design and implementation of a protocol for acquisition and processing of infrared images obtained from hands

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