Development of a Novel Automated Hair Counting System for the Quantitative Evaluation of Laser Hair Removal.
Abstract
[OBJECTIVE] We aimed to develop and validate a novel computer-assisted automated hair counting system for the quantitative evaluation of laser hair removal (LHR).
[METHODS] We developed a computer-aided image processing system to count hairs on shaved skin and validated its performance through clinical trials. Five volunteers of Fitzpatrick skin type III-IV volunteered and were tested on both thighs. The system automatically detects hair and places a "+" sign on each hair site for every positive detection. This method allows clinicians to check whether a hair has been counted or not. We analyzed the difference in the hair counts between the proposed system (automatic) and those by human observers (manual).
[RESULTS] The hair counts from the proposed system and the manual counts were compared. The percentage error between automatic and manual counting was <5% in each subject. The data of the two groups were statistically verified with Student's independent t-test. The averages were statistically equivalent between the two groups. The proposed system showed significant time saving in terms of counting.
[CONCLUSIONS] A dependable, accurate, and fast method of counting hairs on shaved skin through a computer-aided image processing system was developed and validated. The "+" signs on the image to indicate detection allows clinicians to compare with the original image and detect any omission or redundancy. The proposed system is expected to be reliable in analyzing the results of multiple skin-related treatments, including LHR and hair transplantation. Further, it is expected to be widely applicable for use in the clinic.
[METHODS] We developed a computer-aided image processing system to count hairs on shaved skin and validated its performance through clinical trials. Five volunteers of Fitzpatrick skin type III-IV volunteered and were tested on both thighs. The system automatically detects hair and places a "+" sign on each hair site for every positive detection. This method allows clinicians to check whether a hair has been counted or not. We analyzed the difference in the hair counts between the proposed system (automatic) and those by human observers (manual).
[RESULTS] The hair counts from the proposed system and the manual counts were compared. The percentage error between automatic and manual counting was <5% in each subject. The data of the two groups were statistically verified with Student's independent t-test. The averages were statistically equivalent between the two groups. The proposed system showed significant time saving in terms of counting.
[CONCLUSIONS] A dependable, accurate, and fast method of counting hairs on shaved skin through a computer-aided image processing system was developed and validated. The "+" signs on the image to indicate detection allows clinicians to compare with the original image and detect any omission or redundancy. The proposed system is expected to be reliable in analyzing the results of multiple skin-related treatments, including LHR and hair transplantation. Further, it is expected to be widely applicable for use in the clinic.
추출된 의학 개체 (NER)
| 유형 | 영어 표현 | 한국어 / 풀이 | UMLS CUI | 출처 | 등장 |
|---|---|---|---|---|---|
| 시술 | hair transplantation
|
모발이식 | dict | 1 | |
| 해부 | hair
|
scispacy | 1 | ||
| 해부 | skin
|
scispacy | 1 | ||
| 해부 | thighs
|
scispacy | 1 | ||
| 해부 | hairs
|
scispacy | 1 | ||
| 약물 | [OBJECTIVE]
|
scispacy | 1 | ||
| 약물 | [CONCLUSIONS] A
|
scispacy | 1 | ||
| 질환 | Fitzpatrick skin type III-IV
|
scispacy | 1 | ||
| 기타 | Hair
|
scispacy | 1 | ||
| 기타 | LHR
→ laser hair removal
|
scispacy | 1 | ||
| 기타 | human
|
scispacy | 1 |
MeSH Terms
Automation; Clinical Trials as Topic; Evaluation Studies as Topic; Female; Hair; Hair Removal; Healthy Volunteers; Humans; Image Processing, Computer-Assisted; Laser Therapy; Male; Statistics, Nonparametric
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