Measurement system, method for generating learning model to be used when performing image measurement of semiconductor including predetermined structure, and recording medium for storing program for causing computer to execute processing for generating learning model to be used when performing image measurement of semiconductor including predetermined structure

Patent metadata

Field	Value
Publication number	US-12198327-B2
Application number	US-201917634805-A
Country	US
Kind code	B2
Filing date	Aug 30, 2019
Priority date	Aug 30, 2019
Publication date	Jan 14, 2025
Grant date	Jan 14, 2025

Abstract

The present invention proposes a technique for enabling the execution of measurement processing without referring to a design drawing for which it is difficult to adjust or obtain parameters for image processing that requires knowhow. This measurement system according to the present disclosure refers to a learning model generated on the basis of teaching data, which is generated from a sample image of a semiconductor, and the sample image, generates a region-segmented image from an input image (measurement subject) of a semiconductor having a predetermined structure, and uses the region-segmented image to perform image measurement. Here, the teaching data is an image in which labels, which include a structure of the semiconductor in the sample image, are assigned to each pixel of the image, and the learning model includes parameters for deducing teaching data from the sample image (see indicator 1).

First claim

The invention claimed is:

1. A measurement system that performs image measurement of a semiconductor having a periodical structure, comprising:
at least one processor that performs various processes relating to the image measurement; and
an output device that outputs a result of the image measurement, wherein
the at least one processor performs
a process of generating training data from a sample image of the semiconductor,
a process of generating a learning model based on the sample image and the training data,
a process of generating a region-segmented image from an input image relating to the semiconductor based on the learning model,
a measurement process of performing the image measurement using the region-segmented image, and
a process of outputting a result of the measurement process to the output device,
the training data is an image in which a label including a structure of the semiconductor in the sample image is assigned to each of pixels of the image,
the learning model includes a parameter for inferring the training data or the region-segmented image from the sample image or the input image,
the sample image and the training data are smaller than the input image and include an image region corresponding to the periodical structure, and
the at least one processor generates the parameter of the learning model from the sample image and the training data in the process of generating the learning model.

2. The measurement system according to claim 1 , wherein the learning model is a machine learning model that refers to a region present near each of the pixels in the input image in order to determine the label assigned to each of the pixels.

3. The measurement system according to claim 1 , wherein the learning model is a convolution neural network.

4. The measurement system according to claim 1 , wherein the image region corresponds to a structure of at least one period in the periodical structure.

5. A measurement system that performs image measurement of a semiconductor having a predetermined structure, comprising:
at least one processor that performs various processes relating to the image measurement; and
an output device that outputs a result of the image measurement, wherein
the at least one processor performs
a process of generating training data from a sample image of the semiconductor,
a process of generating a learning model based on the sample image and the training data,
a process of generating a region-segmented image from an input image relating to the semiconductor based on the learning model,
a measurement process of performing the image measurement using the region-segmented image, and
a process of outputting a result of the measurement process to the output device,
the training data is an image in which a label including a structure of the semiconductor in the sample image is assigned to each of pixels of the image,
the learning model includes a parameter for inferring the training data or the region-segmented image from the sample image or the input image,
the at least one processor performs a process of segmenting the region-segmented image into small regions of an image size smaller than the region-segmented image according to the label and grouping the small regions based on types of the small regions, and
the at least one processor performs overlay measurement from the center of gravity of each of the grouped small regions as the measurement process.

6. A measurement system that performs image measurement of a semiconductor having a predetermined structure, comprising:
at least one processor that performs various processes relating to the image measurement; and
an output device that outputs a result of the image measurement, wherein
the at least one processor performs
a process of generating training data from a sample image of the semiconductor,
a process of generating a learning model based on the sample image and the training data,
a process of generating a region-segmented image from an input image relating to the semiconductor based on the learning model,
a measurement process of performing the image measurement using the region-segmented image, and
a process of outputting a result of the measurement process to the output device,
the training data is an image in which a label including a structure of the semiconductor in the sample image is assigned to each of pixels of the image,
the learning model includes a parameter for inferring the training data or the region-segmented image from the sample image or the input image,
the sample image includes a combination of images under different imaging conditions obtained by imaging the same position on the semiconductor under the different imaging conditions a plurality of times, and
the at least one processor generates the training data from the sample image according to the different imaging conditions and generates the learning model based on the training data generated according to the imaging conditions and the sample image.

7. A measurement system that performs image measurement of a semiconductor having a predetermined structure, comprising:
at least one processor that performs various processes relating to the image measurement; and
an output device that outputs a result of the image measurement, wherein
the at least one processor performs
a process of generating training data from a sample image of the semiconductor,
a process of generating a learning model based on the sample image and the training data,
a process of generating a region-segmented image from an input image relating to the semiconductor based on the learning model,
a measurement process of performing the image measurement using the region-segmented image, and
a process of outputting a result of the measurement process to the output device,
the training data is an image in which a label including a structure of the semiconductor in the sample image is assigned to each of pixels of the image,
the learning model includes a parameter for inferring the training data or the region-segmented image from the sample image or the input image,
the imaging under the different imaging conditions includes at least one of imaging with different acceleration voltages, capturing different types of electron images, and changing a synthesis ratio for generation of a synthesized image of different types of electron images.

8. A measurement system that performs image measurement of a semiconductor having a predetermined structure, comprising:
at least one processor that performs various processes relating to the image measurement; and
an output device that outputs a result of the image measurement, wherein
the at least one processor performs
a process of generating training data from a sample image of the semiconductor,
a process of generating a learning model based on the sample image and the training
a process of generating a region-segmented image from an input image relating to the semiconductor based on the learning model,
a measurement process of performing the image measurement using the region-segmented image, and
a process of outputting a result of the measurement process to the output device,
the training data is an image in which a label including a structure of the semiconductor in the sample image is assigned to each of pixels of the image,
the learning model includes a parameter for inferring the training data or the region-segmented image from the sample image or the input image,
the at least one processor segments the sample image into two or more sample image groups, assigns the label to an image included in a first sample image group to generate first training data, generates an intermediate learning model based on the image of t

Assignees

• Hitachi High Tech Corp

Inventors

• Yumiba Ryou
• Sakai Kei
• Yamaguchi Satoru

Classifications

• G06T2207/30148

  Semiconductor; IC; Wafer · CPC title

• G06T2207/20084

  Artificial neural networks [ANN] · CPC title

• G06T2207/20081

  Training; Learning · CPC title

• G06T2207/20021

  Dividing image into blocks, subimages or windows · CPC title

• G01N21/9505

  Wafer internal defects, e.g. microcracks · CPC title