Abstract: A defect observation device detects a defect with high accuracy regardless of a defect size. One imaging configuration for observing an observation target on a sample is selected from an optical microscope, an optical microscope, and an electron microscope, and an imaging condition of the selected imaging configuration is controlled.

Abstract: It is an object of the present invention to provide an antibody specifically binding to GPR20-positive tumor cells such as GIST, a pharmaceutical product comprising the antibody and having therapeutic effects on a tumor, a method for treating a tumor using the aforementioned pharmaceutical product, and the like. It is another object of the present invention to provide an anti-GPR20 antibody having internalization activity, an antibody-drug conjugate containing the antibody, and the like.

Abstract: To quantify the degree of a defect, and provide information useful for yield management. Disclosed is a defect quantification method wherein: a defect image is classified; a measurement region and a measurement area are set to each of the defect image and a reference image on the basis of defect image classification results, said reference image corresponding to the defect image; and an evaluation value of a defect is calculated using each of the measurement values obtained from each of the measurement areas of the defect image and the reference image, and the defect is quantified.

Abstract: Provided is a defect classification apparatus classifying images of defects of a sample included in images obtained by capturing the sample, the apparatus including an image storage unit for storing the images of the sample acquired by an external image acquisition unit, a defect class storage unit for storing types of defects included in the images of the sample, an image processing unit for extracting images of defects from the images from the sample, processing the extracted images of defects and generating a plurality of defect images, a classifier learning unit for learning a defect classifier using the images of defects of the sample extracted by the image processing unit and data of the plurality of generated defect images, and a defect classification unit for processing the images of the sample by using the classifier learned by the classifier learning unit, to classify the images of defects of the sample.

Abstract: An inspection method uses a charged particle microscope to observe a sample and view a defect site or a circuit pattern. A plurality of images is detected by a plurality of detectors and a mixed image is generated by automatically adjusting and mixing weighting factors required when the plurality of images are synthesized with each other. The sample is irradiated and scanned with a charged particle beam so that the plurality of detectors arranged at different positions from the sample detects a secondary electron or a reflected electron generated from the sample. The mixed image is generated by mixing the plurality of images of the sample with each other for each of the plurality of detectors, which are obtained by causing each of the plurality of detectors arranged at the different positions to detect the secondary electron or the reflected electron. The generated mixed image is displayed on a screen.

Abstract: Provided is a GUI including: an unadded pane region that hierarchically displays folders which are sets of images having no class information added thereto; an image pane region that displays the images displayed in the unadded pane region, the displayed images having no classification added thereto; and a class pane region that displays images having classification added thereto, wherein by externally inputting class information for one image having the class information added thereto, the input class information is displayed.

Abstract: In a scheme for analyzing low magnification defect images and determining whether or not a defect detection method using cell comparison is applicable, if a defect detection method using cell comparison cannot be applied and the proportion transitioning to a defect detection method using die comparison increases, throughput may decrease even more than starting out with defect detection by a defect detection method using die comparison. The purpose of present invention is to carry out high precision defect detection with a stable throughput. In the present invention, the defect detection processing mode applied for detecting defects from the defect image is determined using a reference image, and defects are detected from the defect image by the defect detection processing mode that has been determined.

Abstract: In a scheme for analyzing low magnification defect images and determining whether or not a defect detection method using cell comparison is applicable, if a defect detection method using cell comparison cannot be applied and the proportion transitioning to a defect detection method using die comparison increases, throughput may decrease even more than starting out with defect detection by a defect detection method using die comparison. The purpose of present invention is to carry out high precision defect detection with a stable throughput. In the present invention, the defect detection processing mode applied for detecting defects from the defect image is determined using a reference image, and defects are detected from the defect image by the defect detection processing mode that has been determined.

Abstract: A defect image classification apparatus includes a control unit that selects images obtained from at least some detectors among a plurality of detectors, associated with kinds of defects to be a classification result of an automatic defect classification processing unit, as images displayed initially on a display unit. The control unit associates the kinds of the defects and the images displayed initially on the display unit, on the basis of a switching operation log when a user classifies images of defects determined previously as the same kinds as the kinds of the defects determined by the automatic defect classification processing unit.

Abstract: A sample observation device images a sample placed on a movable table by irradiating and scanning the sample with a charged particle beam of a microscope. A degraded image having poor image quality and a high quality image having satisfactory image quality which are acquired at the same location of the sample by causing the charged particle microscope to change an imaging condition for imaging the sample are stored. An estimation process parameter is calculated for estimating the high quality image from the degraded image by using the stored degraded image and high quality image. A high quality image estimation unit processes the degraded image obtained by causing the charged particle microscope to image the desired site of the sample by using the calculated estimation process parameter. Thereby, the high quality image obtained at the desired site is estimated, and then the estimated high quality image is output.

Abstract: In a defect classification operation in which ADC and visual classification are both used, a problem with the visual classification in the related art is solved, and then the high-reliability performance evaluation of the ADC and the update of the ADC learning data set are made possible, using both the ADC and the visual classification, or both the ADC and one other classification apparatus.

Abstract: In order to reduce the amount of time it takes to collect images of defects, this defect inspection device is provided with the following: a read-out unit that reads out positions of defects in a semiconductor wafer that have already been detected; a first imaging unit that takes, at a first magnification, a reference image of a chip other than the chip where one of the read-out defects is; a second imaging unit that takes, at the first magnification, a first defect image that contains the read-out defect; a defect-position identification unit that identifies the position of the defect in the first defect image taken by the second imaging unit by comparing said first defect image with the reference image taken by the first imaging unit; a third imaging unit that, on the basis of the identified defect position, takes a second defect image at a second magnification that is higher than the first magnification; a rearrangement unit that rearranges the read-out defects in an order corresponding to a path that goes

Abstract: An inspection method uses a charged particle microscope to observe a sample and view a defect site or a circuit pattern. A plurality of images is detected by a plurality of detectors and a mixed image is generated by automatically adjusting and mixing weighting factors required when the plurality of images are synthesized with each other. The sample is irradiated and scanned with a charged particle beam so that the plurality of detectors arranged at different positions from the sample detects a secondary electron or a reflected electron generated from the sample. The mixed image is generated by mixing the plurality of images of the sample with each other for each of the plurality of detectors, which are obtained by causing each of the plurality of detectors arranged at the different positions to detect the secondary electron or the reflected electron. The generated mixed image is displayed on a screen.

Abstract: When contamination or local electrification is generated during acquisition of a low-magnification image, if a high-magnification image contains both a portion in which the contamination or local electrification is generated and a portion in which the contamination or local electrification is not generated, a region whose image quality has changed due to the contamination or local electrification is erroneously recognized as a defect. Thus, defect detection fails or it may be impossible to correctly determine the feature quantity of a defect. The invention provides a defect observation system that acquires sample images at a low magnification and a high magnification, and sets the position or size of the field of view of the high-magnification image or the electron beam irradiation range during acquisition of the low-magnification image no that the image acquired at the high magnification does not contain the outer edge of the image acquired at the low magnification.

Abstract: To quantify the degree of a defect, and provide information useful for yield management. Disclosed is a defect quantification method wherein: a defect image is classified; a measurement region and a measurement area are set to each of the defect image and a reference image on the basis of defect image classification results, said reference image corresponding to the defect image; and an evaluation value of a defect is calculated using each of the measurement values obtained from each of the measurement areas of the defect image and the reference image, and the defect is quantified.

Abstract: The purpose of the present invention is to easily extract, from samples to be observed, defect candidates that can be labeled as a defect or “nuisance” (a part for which a manufacturing tolerance or the like is erroneously detected) and to allow parameters pertaining to observation processing to be easily adjusted. This defect observation method comprises: an imaging step to image, on the basis of defect information from an inspection device, an object to be inspected and obtain a defect image and a reference image corresponding to the defect image; a parameter determining step to determine a first parameter to be used in the defect extraction by using a first feature set distribution acquired from the reference image and the defect image captured in the imaging step and a second feature net distribution acquired from the reference image; and an observing step to observe using the first parameter determined in the parameter determining step.

Abstract: A method for reviewing a defect including a light capturing step that illuminates a sample with light under plural optical conditions, while varying only at least one of illumination conditions, sample conditions, or detection conditions, and detects plural lights scattering from the sample; a signal obtaining step that obtains plural signals based on the lights detected; and a processing step that discriminates a defect from noise according to a waveform characteristic quantity, an image characteristic quantity, or a value characteristic quantity created using the signals and derives the coordinates of defect.

Abstract: The present invention provides a charged-particle radiation apparatus with a defect observation device for observing defects on a sample, the apparatus including a control unit and a display unit. The control unit is configured to execute a drift correction process on one or more images acquired with the defect observation device under a plurality of correction conditions, and display the plurality of correction conditions and a plurality of corrected images obtained through execution of the drift correction process in association with each other, as a first screen on the display unit.

Abstract: Conventionally, there was no method for automatically selecting the layers to be overlaid, so when the number of layers to be overlaid was large, there was a problem that much time was required for selecting the layers. It is an object of the present invention to provide a defect image analysis method capable of specifying patterns and layers in which a defect occurs by overlaying defect images to be analysis targets and design layout data, and a defect image analysis system capable of improving the efficiency to select the layers from the design layout data. The present invention is characterized in dividing analysis target images for each hierarchy corresponding to a manufacturing process and generating a plurality of layers; calculating a degree of matching between each of the layer division images and each design layer of the design layout data; and specifying a design layer with a highest degree of matching of the each design layer as a design layer corresponding to the layer division image.

Abstract: Cases in which defects are analyzed in a manufacturing process stage in which a pattern is not formed or in a manufacturing process in which a pattern formed on a lower layer does not appear in the captured image are increasing. However, in these cases, there is a problem of not being able to synthesize a favorable reference image and failing to detect a defect when a periodic pattern cannot be recognized in the pattern. In the present invention, a defect occupation rate, which is the percentage of an image being inspected occupied by a defect region, is found, it is determined whether the defect occupation rate is higher or lower than a threshold, and, in accordance with the determination results, it is determined whether to create, as the reference image, an image comprising pixels having the average luminance value of the luminance values of a plurality of pixels contained in the image being inspected.