Computer vision-based system for early diagnosis of stereoscopic vision alterations

ABSTRACT

Stereopsis is the three-dimensional perception capability, which is possible when binocular vision is present. Development of binocular vision system ends around 7-year-old, and after this time brain connections are already set, therefore, it will be difficult to recover stereopsis. Early diagnosis of Stereoscopic Visual Alterations (SVA) in the childhood is paramount to receive an appropriate treatment as soon as possible. Currently, to detect SVA, ophthalmologists commonly carry out tests based on cards. All these tests are based on the random-dot-stereogram principle, with different seconds of arc images, which allows doctors to graduate stereopsis. Some limits of this tests have been identified, such as monocular clues (e.g., the contours of the objects), or the non-standardized range levels depending on the test. This paper presents a novel concept of measuring stereopsis based on computer vision techniques. The system detects SVA in patients and calculates the degree of the perceived depth. As early diagnosis of SVA may suppose a therapeutic possibility, this platform is aimed at children by using stereoscopic models with varied and attractive designs. To validate the proposal, an early-stage prototype has been implemented and an objective evaluation of the measurement accuracy and reliability has been carried out with satisfactory results.

KEYWORDS:

• Clinical decision support system
• computer vision
• medical information system
• stereoscopic vision alterations

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

¹ https://www.intel.com/content/dam/support/us/en/documents/emerging-technologies/intel-realsense-technology/Intel-RealSense-D400-Series-Datasheet.pdf.

² Spanish health card identifier.

Additional information

Funding

This work was supported by the Universitat Politècnica de València and Fundació per al Foment de la Investigació Sanitària i Biomèdica de la Comunitat Valenciana UPVFISABIO- 2019-B19 under Grant UPV-FISABIO-2019-B19.