Surgical planning for horizontal strabismus using Support Vector Regression

• This work investigates computational methods for horizontal strabismus surgeries.
• Our approach used Support Vector Regression to estimate the surgical plan.
• We used data from the records of 114 patients with horizontal/vertical strabismus.
• For the medial rectus muscles, the mean error was 0.5 mm for recoil and 0.7 for resection.
• For the lateral rectus muscles, the mean error was 0.6 for recoil and 0.8 for resection.

Strabismus is a pathology which affects about 4% of the population, causing esthetic problems (reversible at any age) and irreversible sensory disorders, altering the vision mechanism. Many techniques can be applied to settle the muscular balance, thus eliminating strabismus. However, when the conservative treatment is not enough, the surgical treatment is adopted, applying recoils or resections to the ocular muscles affected. The factors involved in the surgical strategy in cases of strabismus are complex, demanding both theoretical knowledge and experience from the surgeon. So, the present work proposes a methodology based on Support Vector Regression to help the physician with decision related to horizontal strabismus surgeries. The efficiency of the method at the indication of the surgical plan was evaluated through the average difference between the values that it provided and the values indicated by the specialists. In the planning of medial rectus muscles surgeries, the average error was 0.5 mm for recoil and 0.7 for resection. For lateral rectus muscles, the mean error was 0.6 for recoil and 0.8 for resection. The results are promising and prove the feasibility of the use of Support Vector Regression in the indication of strabismus surgeries.