Abstract: A method implemented in an ophthalmic surgical laser system that employs a resonant scanner, scan line rotator, and XY- and Z-scanners, for forming a corneal flap in a patient's eye with improved bubble management during each step of the flap creation process. A pocket cut is formed first below bed level, followed by the bed connected to the pocket cut, then by a side cut extending from the bed to the anterior corneal surface. The pocket cut includes a pocket region located below the bed level and a ramp region connecting the pocket region to the bed. The bed is formed by a hinge cut and a first ring cut at lower laser energies, followed by a bed cut and then a second ring cut, which ensures that any location in the flap bed is cut twice to minimize tissue adhesion. The side cut is formed by multiple side-cut layers at different depths which are joined together. All cuts are formed by scanning a laser scan line generated by the resonant scanner.

Abstract: An ophthalmic surgical laser system and method for forming a lenticule in a subject's eye using “fast-scan-slow-sweep” scanning scheme. A high frequency scanner forms a fast scan line, which is placed by the XY and Z scanners at a location tangential to a parallel of latitude of the surface of the lenticule. The XY and Z scanners then move the scan line in a slow sweep trajectory along a meridian of longitude of the surface of the lenticule in one sweep. Multiple sweeps are performed along different meridians to form the entire lenticule surface, and a prism is used to change the orientation of the scan line of the high frequency scanner between successive sweeps. In each sweep, within a central area of the lenticule where the sweeps overlap, the laser is periodically blanked (or delivered with significantly reduced pulse energy) to reduce the total energy delivered in that area.

Abstract: A method implemented in an ophthalmic surgical laser system that employs a resonant scanner, scan line rotator, and XY- and Z-scanners, for forming a corneal flap in a patient's eye with improved bubble management during each step of the flap creation process. A pocket cut is formed first below bed level, followed by the bed connected to the pocket cut, then by a side cut extending from the bed to the anterior corneal surface. The pocket cut includes a pocket region located below the bed level and a ramp region connecting the pocket region to the bed. The bed is formed by a hinge cut and a first ring cut at lower laser energies, followed by a bed cut and then a second ring cut, which ensures that any location in the flap bed is cut twice to minimize tissue adhesion. The side cut is formed by multiple side-cut layers at different depths which are joined together. All cuts are formed by scanning a laser scan line generated by the resonant scanner.

Abstract: In laser-assisted corneal lenticule extraction procedures, the lenticule incision profile includes anterior and posterior lenticule incisions, with one or more of the following features: plano transition zone outside the optical zone, to improve mating of anterior and posterior incision surfaces after lenticule extraction; shallow arcuate incisions above the anterior incision and near the lenticule edge, to improve surface mating; separate ring cut intersecting the anterior and posterior incisions in the transition zone, to reduce tissue bridges and minimize tear at the lenticule edges and facilitate easy lenticule extraction; larger posterior incision, which includes a pocket zone outside the lenticule edge, for better surface mating and bubble management during cutting; and a separate ring shaped pocket cut intersecting the pocket zone of the posterior incision, for bubble management.

Abstract: A motor position compensation method for an ophthalmic surgical laser system employs a deep artificial neural network to characterize motor following errors of the motors of the system. The artificial neural network is trained using a large number of commanded motor positions and corresponding measured actual motor positions (measured by encoders associated with the motors) as training data, to obtain a trained artificial neural network that can predict the actual motor position for any commanded motor position. Before executing a treatment scan, the original commanded motor positions calculated from the intended scan pattern are inputted to the trained artificial neural network to predict the actual motor positions, and the predicted actual motor positions are used to adjust the original commanded motor positions. The adjusted commanded motor positions are then used to perform the treatment scan, which produces an actual scan pattern that more closely match the intended scan pattern.