Reticle & photomask defect review
Locate missing features, pinholes, particles, and pattern deviations in reticle and photomask images.
Example outputs shown for illustration. Numbers depend on your samples and protocol.
Image: Illustrative rendering (AI-generated, gpt-image-2), not an inspection image of a specific mask
What you get
The measurement, today
Mask defects are often reviewed against reference imagery by hand. A finding may be obvious in a field yet difficult to quantify, classify, and retain for later comparison.
What it costs
A reticle defect can print repeatedly across a wafer. Early image review helps teams separate candidates for engineering review from cosmetic or imaging artifacts.
From image to reviewed result
- 1
Load inspection fields
Provide brightfield, darkfield, or microscope images with the reference pattern or a known-good field.
- 2
Align the pattern
Register repeated structures so missing, extra, and displaced features can be localized.
- 3
Classify candidates
Separate pattern deviations, pinholes, opaque particles, and image artifacts for review.
- 4
Export review evidence
Deliver a location-indexed list with the original and annotated inspection fields.
Scope: Supports image-based defect review. Mask disposition, printability, and any repair decision require the qualified inspection and lithography process used by your organization.
Related applications
Photoresist pattern defects
Detect resist pattern collapse, bridging, footing, and scumming after develop.
Critical dimension (CD) metrology
Line width, space, and via diameter measured from top-down images, with per-feature tables.
Semiconductor defect patterns
Classify wafer-map patterns and quantify defect clusters and densities.
Send a sample image and a measurement goal
We will show the closest ConductVision workflow and flag what needs custom validation for your images.
