P Vallotton1, N Thomas. 1. Biotech Imaging, CSIRO Mathematical and Information Sciences, North Ryde, NSW, Australia. pascal.vallotton@csiro.au
Abstract
BACKGROUND/ PURPOSE: Hair loss or hair excess is a common condition. There is a growing need to quantitatively assess the success of interventions aimed at replenishing areas that lack hair or at removing hair from areas such as the back, the legs, or the arms. Non-invasive methods that do not require staining are highly desirable because the staining process itself may affect the efficacy of the treatment. METHODS: We introduce a system based on a flatbed scanner and on novel and sensitive image analysis algorithms to count the number of hairs and their individual length. Additionally, a measure of hair visibility is introduced, which allows assessing objectively the severity of the condition. RESULTS: Our system is able to detect even hairs that are difficult to see to a human observer. It is robust to skin impurities or variations in the skin texture and colour. Scanner imaging ensures a sharp image over the whole field. The system analyses on the order of two images per minute, making it suitable for large clinical studies. Counts delivered by a human counter vs. the software were within 10% of each other (N=12). CONCLUSION: Based on our results, we expect that the software will be useful to a number of researchers investigating medical and cosmetic issues involving objective assessment of pilosity. The algorithm itself may be of use for other applications.
BACKGROUND/ PURPOSE:Hair loss or hair excess is a common condition. There is a growing need to quantitatively assess the success of interventions aimed at replenishing areas that lack hair or at removing hair from areas such as the back, the legs, or the arms. Non-invasive methods that do not require staining are highly desirable because the staining process itself may affect the efficacy of the treatment. METHODS: We introduce a system based on a flatbed scanner and on novel and sensitive image analysis algorithms to count the number of hairs and their individual length. Additionally, a measure of hair visibility is introduced, which allows assessing objectively the severity of the condition. RESULTS: Our system is able to detect even hairs that are difficult to see to a human observer. It is robust to skin impurities or variations in the skin texture and colour. Scanner imaging ensures a sharp image over the whole field. The system analyses on the order of two images per minute, making it suitable for large clinical studies. Counts delivered by a human counter vs. the software were within 10% of each other (N=12). CONCLUSION: Based on our results, we expect that the software will be useful to a number of researchers investigating medical and cosmetic issues involving objective assessment of pilosity. The algorithm itself may be of use for other applications.