Computer Imaging of Alopecia Areata and Scalp Detection: A Survey
| Computer Imaging of Alopecia Areata and Scalp Detection: A Survey | ||
|   |  | |
| © 2022 by IJETT Journal | ||
| Volume-70 Issue-8 | ||
| Year of Publication : 2022 | ||
| Authors : C. Saraswathi, B. Pushpa | ||
| DOI : 10.14445/22315381/IJETT-V70I8P236 | ||
How to Cite?
 
C. Saraswathi, B. Pushpa, "Computer Imaging of Alopecia Areata and Scalp Detection: A Survey," International Journal of Engineering Trends and Technology, vol. 70, no. 8, pp. 347-358, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I8P236
Abstract
Alopecia Areata (AA) is a frequent inflammatory affliction that causes erratic Hair Loss (HL). As with other 
resistant-influenced disorders, the development of AA is assumed to be the result of a complicated balance between 
surroundings and heredity. Various factors can cause hair loss, and trichoscopies and biopsies are usually required to 
ensure the cause of AA. There is currently no remedy for AA, although doctors can recommend various medications to 
support hair regrowth rapidly. AA does not immediately cause illness and is not communicable, but it is tough to adjust 
psychologically. Further, many people's experience with AA is regarded as a terrible infection that needs counselling for 
the mental and physical components of HL. So, an efficient HL detection system should be developed to tackle this 
emotional perceptive. Detecting the AA detection with scalp condition is required to find out the cause of AA level and can 
provide guidance for proper treatment. Computer vision using deep learning techniques is gaining significant attention 
because of improved performance over previous approaches. This article presents detailed analyses of different AA 
detection approaches using (Artificial Intelligence) AI techniques with modern Deep learning. First, AI-based frameworks 
designed by researchers in the past for different AA are studied briefly. After that, a comparative study is conducted to 
understand those frameworks' drawbacks and suggest new solutions to improve the AA detection system.
 
Keywords
Artificial Intelligence, Alopecia Areata, Hair Loss (HL), Scalp Condition, Detection System. 
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