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The curvilinear mask has received significant attention in recent years due to its capacity to provide superior lithography image quality in advanced nodes. Within the framework of curvilinear mask optical proximity correction (OPC), the selection and manipulation of control points are two pivotal steps. However, the existing methods employed in curvilinear mask OPC are characterized by complex algorithms, and the fidelity of print images is often suboptimal. To address these challenges, this paper employs a tangent angle-arc length (TAAL) curve, a one-dimensional function, to represent the two-dimensional mask boundary. The TAAL curve simplifies the process of control point selection and facilitates the determination of movement directions, thereby mitigating computational complexity. In addition, based on the TAAL curve, the small selection with directional movement (SSDM) method is introduced. Simulation results demonstrate that the TAAL-based SSDM method significantly reduces pattern errors (PAE) compared to the uniform selection and random movement methods.
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http://dx.doi.org/10.1364/OE.557176 | DOI Listing |
J Med Imaging (Bellingham)
July 2025
National Cancer Institute, Center for Cancer Research, Thoracic and Gastrointestinal Malignancies Branch, Bethesda, Maryland, United States.
Purpose: The Response Evaluation Criteria in Solid Tumors (RECIST) relies solely on one-dimensional measurements to evaluate tumor response to treatments. However, thymic epithelial tumors (TETs), which frequently metastasize to the pleural cavity, exhibit a curvilinear morphology that complicates accurate measurement. To address this, we developed a physician-guided deep learning model and performed a retrospective study based on a patient cohort derived from clinical trials, aiming at efficient and reproducible volumetric assessments of TETs.
View Article and Find Full Text PDFThe curvilinear mask has received significant attention in recent years due to its capacity to provide superior lithography image quality in advanced nodes. Within the framework of curvilinear mask optical proximity correction (OPC), the selection and manipulation of control points are two pivotal steps. However, the existing methods employed in curvilinear mask OPC are characterized by complex algorithms, and the fidelity of print images is often suboptimal.
View Article and Find Full Text PDFAppl Opt
December 2024
Curvilinear mask has received much attention in recent years due to its ability to obtain better image quality in advanced nodes. A common method for optimizing curvilinear mask in optical proximity correction (OPC) flow is moving control points on the edge directly (MCED-based OPC), but it requires storing mass data. This paper uses distance-versus-angle signature (DVAS), a one-dimensional function, to represent a two-dimensional boundary of mask.
View Article and Find Full Text PDFMar Pollut Bull
June 2024
The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China; University of Chinese Academy of Sciences, Beijing, China; Guangdong Provincial Key Laboratory of Brain Connectome and Behavior, CAS Key Laboratory of Brain Conne