Automatic diagnosis of strabismus in digital videos through cover test. (March 2017)
- Record Type:
- Journal Article
- Title:
- Automatic diagnosis of strabismus in digital videos through cover test. (March 2017)
- Main Title:
- Automatic diagnosis of strabismus in digital videos through cover test
- Authors:
- Valente, Thales Levi Azevedo
de Almeida, João Dallyson Sousa
Silva, Aristófanes Corrêa
Teixeira, Jorge Antonio Meireles
Gattass, Marcelo - Abstract:
- Highlights: This work investigates computational method for automatic diagnose of strabismus. The strabismus was detected in digital video through the Cover Test. The method uses image and video processing and requires only a digital camera and a regular computer. The method achieved 87% of accuracy in diagnosing strabismus. The overall average error was lower than 1 Δ, and an average error of 2.6 Δ in deviation measure. Abstract: Background and Objective: Medical image processing can contribute to the detection and diagnosis of human body anomalies, and it represents an important tool to assist in minimizing the degree of uncertainty of any diagnosis, while providing specialists with an additional source of diagnostic information. Strabismus is an anomaly that affects approximately 4% of the population. Strabismus modifies vision such that the eyes do not properly align, influencing binocular vision and depth perception. Additionally, it results in aesthetic problems, which can be reversed at any age. However, the use of low cost computational resources to assist in the diagnosis and treatment of strabismus is not yet widely available. This work presents a computational methodology to automatically diagnose strabismus through digital videos featuring a cover test using only a workstation computer to process these videos. Methods: The method proposed was validated in patients with exotropia and consists of eight steps: (1) acquisition, (2) detection of the region surroundingHighlights: This work investigates computational method for automatic diagnose of strabismus. The strabismus was detected in digital video through the Cover Test. The method uses image and video processing and requires only a digital camera and a regular computer. The method achieved 87% of accuracy in diagnosing strabismus. The overall average error was lower than 1 Δ, and an average error of 2.6 Δ in deviation measure. Abstract: Background and Objective: Medical image processing can contribute to the detection and diagnosis of human body anomalies, and it represents an important tool to assist in minimizing the degree of uncertainty of any diagnosis, while providing specialists with an additional source of diagnostic information. Strabismus is an anomaly that affects approximately 4% of the population. Strabismus modifies vision such that the eyes do not properly align, influencing binocular vision and depth perception. Additionally, it results in aesthetic problems, which can be reversed at any age. However, the use of low cost computational resources to assist in the diagnosis and treatment of strabismus is not yet widely available. This work presents a computational methodology to automatically diagnose strabismus through digital videos featuring a cover test using only a workstation computer to process these videos. Methods: The method proposed was validated in patients with exotropia and consists of eight steps: (1) acquisition, (2) detection of the region surrounding the eyes, (3) identification of the location of the pupil, (4) identification of the location of the limbus, (5) eye movement tracking, (6) detection of the occluder, (7) identification of evidence of the presence of strabismus, and (8) diagnosis. Results: To detect the presence of strabismus, the proposed method achieved a specificity value of 100%, and (2) a sensitivity value of 80%, with 93.33% accuracy in diagnosis of patients with extropia. This procedure was recognized to diagnose strabismus with an accuracy value of 87%, while acknowledging measures lower than 1 Δ, and an average error in the deviation measure of 2.57 Δ . Conclusions: We demonstrated the feasibility of using computational resources based on image processing techniques to achieve success in diagnosing strabismus by using the cover test. Despite the promising results the proposed method must be validated in a greater volume of video including other types of strabismus. … (more)
- Is Part Of:
- Computer methods and programs in biomedicine. Volume 140(2017)
- Journal:
- Computer methods and programs in biomedicine
- Issue:
- Volume 140(2017)
- Issue Display:
- Volume 140, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 140
- Issue:
- 2017
- Issue Sort Value:
- 2017-0140-2017-0000
- Page Start:
- 295
- Page End:
- 305
- Publication Date:
- 2017-03
- Subjects:
- Diagnosis of strabismus -- Cover test -- Image processing -- Digital videos
Medicine -- Computer programs -- Periodicals
Biology -- Computer programs -- Periodicals
Computers -- Periodicals
Medicine -- Periodicals
Médecine -- Logiciels -- Périodiques
Biologie -- Logiciels -- Périodiques
Biology -- Computer programs
Medicine -- Computer programs
Periodicals
Electronic journals
610.28 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01692607 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cmpb.2017.01.002 ↗
- Languages:
- English
- ISSNs:
- 0169-2607
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.095000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 1692.xml