Carl Zeiss Meditec Gmbh

Kla Tencor Corporation

Carl Zeiss Meditec Ag

Siddharth Srivastava

Stilian Pandev

Utkarsh Sharma

Harihar Narasimha-Iyer

Tilman Schmoll

Wei Guang Lu

Alexandre R Tumlinson

Mary K Durbin

Dzmitry Sanko

Christine N Ritter

Suzanne M Thompson

Raphaël Guilleminot

Jayson Arthur McCauliff

Marc D Stern

Zheen Zhao

Melissa R Horne

Julia Coelho

Methods and systems for measuring overlay error between structures formed on a substrate by successive lithographic processes are presented herein. Two overlay targets, each having programmed offsets in opposite directions are employed to perform an overlay measurement. Overlay error is measured based on zero order scatterometry signals and scatterometry data is collected from each target at two different azimuth angles. In addition, methods and systems for creating an image-based measurement model based on measured, image-based training data are presented. The trained, image-based measurement model is then used to calculate values of one or more parameters of interest directly from measured image data collected from other wafers. The methods and systems for image based measurement described herein are applicable to both metrology and inspection applications.

Signal response metrology for image based and scatterometry overlay measurements

Image based signal response metrology

Improvements to user interfaces for ophthalmic imaging systems, in particular Optical Coherence Tomography (OCT) systems are described to improve how diagnostic data are displayed, analyzed and presented to the user. The improvements include user customization of display and reports, protocol driven work flow, bookmarking of particular B-scans, accessing information from a reference library, customized normative databases, and ordering of follow-up scans directly from a review screen. A further aspect is the ability to optimize the contrast and quality of displayed B-scans using a single control parameter. Virtual real time z-tracking is described that maintains displayed data in the same depth location regardless of motion.

User interface for acquisition, display and analysis of ophthalmic diagnostic data

Methods for analyzing and visualizing OCT angiography data are presented. In one embodiment, an automated method for identifying the foveal avascular zone in a two dimensional en face image generated from motion contrast data is presented. Several 3D visualization techniques are presented including one in which a particular vessel is selected in a motion contrast image and all connected vessels are highlighted. A further embodiment includes a stereoscopic visualization method. In addition, a variety of metrics for characterizing OCT angiography image data are described.

Analysis and visualization of OCT angiography data

Systems and methods for improved acquisition of ophthalmic optical coherence tomography data are presented, allowing for enhanced ease of use and higher quality data and analysis functionality. Embodiments include automated triggering for detecting and initiating collection of OCT ophthalmic data, an automated technique for determining the optimal number of B-scans to be collected to create the highest quality image and optimize speckle reduction, automated review of fundus images collected with an adjunct imaging modality to guide the OCT data collection, a single scan protocol in which a large field of view is collected with HD B-scans embedded at different locations depending on automated analysis of either a fundus image or sparse OCT scan, and various scan configurations for imaging eyes with large axial depth range.

Systems and methods for improved acquisition of ophthalmic optical coherence tomography data

Growing community of inventors

Hayward, CA, United States of America

Siddharth Srivastava