Image-Based Face Recognition Techniques Used in Disease Detection Approaches: A Survey
Facial diseases lead to noticeable changes on the human face, and some of them extend beyond internal effects or organ-based disorders. Indeed, certain types of facial diseases result in visually noticeable abnormalities on the human face. These alterations in facial patterns can serve as potential...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
middle technical university
2024-03-01
|
| Series: | Journal of Techniques |
| Subjects: | |
| Online Access: | https://journal.mtu.edu.iq/index.php/MTU/article/view/1966 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832595118009352192 |
|---|---|
| author | Ghalib Ahmed Salman Inas Jawad Kadhim Ahmed Husham Al-Badri |
| author_facet | Ghalib Ahmed Salman Inas Jawad Kadhim Ahmed Husham Al-Badri |
| author_sort | Ghalib Ahmed Salman |
| collection | DOAJ |
| description |
Facial diseases lead to noticeable changes on the human face, and some of them extend beyond internal effects or organ-based disorders. Indeed, certain types of facial diseases result in visually noticeable abnormalities on the human face. These alterations in facial patterns can serve as potential indicators for corresponding diseases, particularly in the fields of endocrinology and metabolism, Muscles-Nervous disorders, Chromosomes, and Genetic disorders, among others. Technologies used in Face Recognition (FR) have been developed over the past few decades; however, only a limited amount of research has been applied in recent years to FR-based disease detection for clinical purposes. FR applications relying on Artificial Neural Network (ANN) techniques have recorded higher accuracy rates in diagnosing facial diseases. This field of recognition holds promising potential for optimizing facial diagnosis approaches and supporting medical staff in evaluating detections. In practice, only a few research ideas have been translated into medical products, emphasizing the need to identify and integrate future applications. As a primary focus, this paper centers on the key applications and technologies for detecting various types of facial diseases, along with a discussion of prospects.
|
| format | Article |
| id | doaj-art-5d0b15bd25784d6dbe0cd858000c18ea |
| institution | Kabale University |
| issn | 1818-653X 2708-8383 |
| language | English |
| publishDate | 2024-03-01 |
| publisher | middle technical university |
| record_format | Article |
| series | Journal of Techniques |
| spelling | doaj-art-5d0b15bd25784d6dbe0cd858000c18ea2025-01-19T10:58:55Zengmiddle technical universityJournal of Techniques1818-653X2708-83832024-03-016110.51173/jt.v6i1.1966Image-Based Face Recognition Techniques Used in Disease Detection Approaches: A SurveyGhalib Ahmed Salman0Inas Jawad Kadhim1Ahmed Husham Al-Badri2Electrical Engineering Technical College, Middle Technical University, Baghdad, Iraq.Electrical Engineering Technical College, Middle Technical University, Baghdad, Iraq.Faculty of Computing, Universiti Teknologi Malaysia, Johor Bahru, Malaysia Facial diseases lead to noticeable changes on the human face, and some of them extend beyond internal effects or organ-based disorders. Indeed, certain types of facial diseases result in visually noticeable abnormalities on the human face. These alterations in facial patterns can serve as potential indicators for corresponding diseases, particularly in the fields of endocrinology and metabolism, Muscles-Nervous disorders, Chromosomes, and Genetic disorders, among others. Technologies used in Face Recognition (FR) have been developed over the past few decades; however, only a limited amount of research has been applied in recent years to FR-based disease detection for clinical purposes. FR applications relying on Artificial Neural Network (ANN) techniques have recorded higher accuracy rates in diagnosing facial diseases. This field of recognition holds promising potential for optimizing facial diagnosis approaches and supporting medical staff in evaluating detections. In practice, only a few research ideas have been translated into medical products, emphasizing the need to identify and integrate future applications. As a primary focus, this paper centers on the key applications and technologies for detecting various types of facial diseases, along with a discussion of prospects. https://journal.mtu.edu.iq/index.php/MTU/article/view/1966Face RecognitionDisease DetectionArtificial IntelligenceConvolutional Neural NetworkFace Disorders |
| spellingShingle | Ghalib Ahmed Salman Inas Jawad Kadhim Ahmed Husham Al-Badri Image-Based Face Recognition Techniques Used in Disease Detection Approaches: A Survey Journal of Techniques Face Recognition Disease Detection Artificial Intelligence Convolutional Neural Network Face Disorders |
| title | Image-Based Face Recognition Techniques Used in Disease Detection Approaches: A Survey |
| title_full | Image-Based Face Recognition Techniques Used in Disease Detection Approaches: A Survey |
| title_fullStr | Image-Based Face Recognition Techniques Used in Disease Detection Approaches: A Survey |
| title_full_unstemmed | Image-Based Face Recognition Techniques Used in Disease Detection Approaches: A Survey |
| title_short | Image-Based Face Recognition Techniques Used in Disease Detection Approaches: A Survey |
| title_sort | image based face recognition techniques used in disease detection approaches a survey |
| topic | Face Recognition Disease Detection Artificial Intelligence Convolutional Neural Network Face Disorders |
| url | https://journal.mtu.edu.iq/index.php/MTU/article/view/1966 |
| work_keys_str_mv | AT ghalibahmedsalman imagebasedfacerecognitiontechniquesusedindiseasedetectionapproachesasurvey AT inasjawadkadhim imagebasedfacerecognitiontechniquesusedindiseasedetectionapproachesasurvey AT ahmedhushamalbadri imagebasedfacerecognitiontechniquesusedindiseasedetectionapproachesasurvey |