LithoSeg: A Coarse-to-Fine Framework for High-Precision Lithography Segmentation
This addresses the need for robust and precise lithography segmentation to improve semiconductor manufacturing yield, representing a domain-specific incremental advancement.
The paper tackled the problem of high-precision segmentation of lithography SEM images for semiconductor manufacturing by proposing LithoSeg, a coarse-to-fine network that outperformed previous methods in accuracy and metrology precision with less supervision.
Accurate segmentation and measurement of lithography scanning electron microscope (SEM) images are crucial for ensuring precise process control, optimizing device performance, and advancing semiconductor manufacturing yield. Lithography segmentation requires pixel-level delineation of groove contours and consistent performance across diverse pattern geometries and process window. However, existing methods often lack the necessary precision and robustness, limiting their practical applicability. To overcome this challenge, we propose LithoSeg, a coarse-to-fine network tailored for lithography segmentation. In the coarse stage, we introduce a Human-in-the-Loop Bootstrapping scheme for the Segment Anything Model (SAM) to attain robustness with minimal supervision. In the subsequent fine stage, we recast 2D segmentation as 1D regression problem by sampling groove-normal profiles using the coarse mask and performing point-wise refinement with a lightweight MLP. LithoSeg outperforms previous approaches in both segmentation accuracy and metrology precision while requiring less supervision, offering promising prospects for real-world applications.