Abstract: The present application discloses a method of prescribing a scan plane during Magnetic Resonance Imaging (MRI) of an anatomy. The method comprises acquiring a volume image of the anatomy at a first resolution and simultaneously displaying three planar images representing cross-sections through the anatomy. The three images are orthogonal to each other and intersecting at a common point in the volume. The method also comprises further displaying a pair of axes on each image showing a correspondence of the image with each of the other two images, and receiving a manipulation of one at least one of the axes on at least one of the images and automatically updating the other images to maintain the correspondences. The method also comprises acquiring a volume of the anatomy at a second resolution that is higher than the first resolution.

Abstract: The present invention relates to a defect inspection apparatus for inspecting defects in patterns formed on a semiconductor device, on the GUI of which for the confirmation of the inspection results an area is provided for displaying any one of or facing each other the features amount of defects, and the image during inspection or the reacquired image, and on the GUI of which a means is provided for setting the classification class and importance of the defects, and based on the classification class and the importance of the defects information set by this setting means, the classification conditions or the defect judging conditions are automatically or manually set so that the inspection conditions may be set easily.

Abstract: A classification model optimum for realization of a defect classification request by a user is not known by the user. Then, the user sets a classification model which is not necessarily suitable and makes classification, resulting in degradation in classification performance. Therefore, the present invention automatically generates plural potential classification models and combines class likelihoods calculated from the plural classification models to classify. To combine, an index about the adequacy of each model, in other words, an index indicating a reliable level of likelihood calculated from the each potential classification model, is also calculated. Considering the calculated result, the class likelihoods calculated from the plural classification models are combined to execute classification.

Abstract: With little efforts, to estimate the appropriateness of automatic defect classification, and to make classification criteria settable with a guarantee for the better classification performance, defects unknown with their classification classes are classified based on two different classification criteria. Also, defects differed in classification results are collected, and each thereto, a defect classification class is provided by using a manual. Then, the defects provided with the classification classes are divided into two types of groups: one is a setting group for the classification criteria; and the other is an evaluation group. Based on the classification criteria that is so set as to classify the defects included in the setting group with the maximum performance, the classification performance of a case where classification is applied to defects included in the evaluation group is calculated, and the appropriateness of thus set classification criteria is evaluated.

Abstract: The present invention relates to a defect detection or observation method that detects fine defects in the course of defect inspection and observation, does not detect locations not constituting defects, or classifies a defect candidate as a grain phenomenon or other phenomenon that does not affect a product.

Abstract: The present invention provides a method of classifying defects wherein defects are detected in a first inspection machine. The detected defects are then reviewed by a second inspection machine. A sampling rate for review by the second inspection machine is determined by a defect classifier in the first inspection machine.

Abstract: A highly reliable defect automatic classifying method and apparatus capable of flexibly coping with a request for classifying a defect given by each user without having to collect lots of teach data items. A classifying class arrangement is defined by a user by combining classes supplied by the system itself or classes defined by the user and, further, a priori knowledge on the defect class is given by the user as a restriction so as to carry out restricted learning.

Abstract: The present invention provides a mirror electron projection (MPJ) type (SEPJ type included) scanning electron beam apparatus that is capable of performing condition setup, and a method and apparatus for inspecting pattern defects with the scanning electron beam apparatus. A mirror electron projection type defect inspection apparatus, which comprises a charging device for emitting a charging electron beam, electron beam irradiation means for shedding a mirror electron projection electron beam onto an inspection region near which an electrical potential distribution is formed, detection means for detecting secondary electrons or reflected electrons generated from a surface and proximity of the specimen, and defect detection means for detecting a defect by processing a mirror image signal that is detected by the detection means, includes irradiation condition optimization means for optimizing charging electron beam irradiation conditions.

Abstract: The present invention relates to a defect detection or observation method that detects fine defects in the course of defect inspection and observation, does not detect locations not constituting defects, or classifies a defect candidate as a grain phenomenon or other phenomenon that does not affect a product.

Abstract: The present invention relates to a defect detection or observation method that detects fine defects in the course of defect inspection and observation, does not detect locations not constituting defects, or classifies a defect candidate as a grain phenomenon or other phenomenon that does not affect a product.

Abstract: An apparatus and method for electron beam inspection with projection electron microscopy, is constructed so as to allow correction of changes in focus offsets due to changes in the electrically charged state particularly during inspection. The apparatus includes: a focus measure sensor unit; a focus measure calculation unit which calculates focus measure from the multiple image signals converted by the focus measure sensor unit; a focus position calculation unit which calculates the height of a confocal plane conjugate to the plane of convergence of a planar electron beam by an objective lens, on the basis of the calculated focus measure, and then calculates the focus position of the objective lens on the basis of the calculated height of the confocal plane; and a focus position correction unit which corrects the focus position of the objective lens according to the calculated focus position of the objective lens.

Abstract: The present invention provides a mirror electron projection (MPJ) type (SEPJ type included) scanning electron beam apparatus that is capable of performing condition setup, and a method and apparatus for inspecting pattern defects with the scanning electron beam apparatus. A mirror electron projection type defect inspection apparatus, which comprises a charging device for emitting a charging electron beam, electron beam irradiation means for shedding a mirror electron projection electron beam onto an inspection region near which an electrical potential distribution is formed, detection means for detecting secondary electrons or reflected electrons generated from a surface and proximity of the specimen, and defect detection means for detecting a defect by processing a mirror image signal that is detected by the detection means, includes irradiation condition optimization means for optimizing charging electron beam irradiation conditions.

Abstract: For the purpose of reducing a false report and shortening inspection time, an area to be inspected is locally inspected under optimum inspection conditions. In order to avoid the number of detected defects from increasing explosively, and thereby to facilitate control of a critical defect, general-purpose layout data, which is used for producing a mask of a semiconductor wafer, is accumulated in a design information server 2. With reference to the layout data, an area to be inspected, which is inspected by a pattern inspecting apparatus 1, is divided into partial inspection areas including a cell portion and a non-cell portion. Inspection parameters are set for each of the partial inspection areas. In addition, the defect reviewing apparatus 8 obtains an inspection result of the pattern inspecting apparatus 1.

Abstract: An apparatus and a method for automatically inspecting a defect by an electron beam using an X-ray detector. The composition of a defective portion is analyzed with higher rapidity and the cause of the defect is easily and accurately determined based on an X-ray spectrum. The X-ray spectrum and the image of foreign particles formed on a process QC wafer are registered as reference data, and the defects generated on a process wafer are classified by collation with the reference data. The use of both the X-ray spectrum and the detected image optimizes the operating conditions for X-ray detection. A defect of which the X ray is to be detected is selected based on the result of classification of defect images automatically collected, and the defect is classified according to the features including both the composition and the external appearance.

Abstract: An apparatus and method for electron beam inspection with projection electron microscopy, is constructed so as to allow correction of changes in focus offsets due to changes in the electrically charged state particularly during inspection. The apparatus includes: a focus measure sensor unit; a focus measure calculation unit which calculates focus measure from the multiple image signals converted by the focus measure sensor unit; a focus position calculation unit which calculates the height of a confocal plane conjugate to the plane of convergence of a planar electron beam by an objective lens, on the basis of the calculated focus measure, and then calculates the focus position of the objective lens on the basis of the calculated height of the confocal plane; and a focus position correction unit which corrects the focus position of the objective lens according to the calculated focus position of the objective lens.

Abstract: The present invention relates to a defect inspection apparatus for inspecting defects in patterns formed on a semiconductor device, on the GUI of which for the confirmation of the inspection results an area is provided for displaying any one of or facing each other the features amount of defects, and the image during inspection or the reacquired image, and on the GUI of which a means is provided for setting the classification class and importance of the defects, and based on the classification class and the importance of the defects information set by this setting means, the classification conditions or the defect judging conditions are automatically or manually set so that the inspection conditions may be set easily.

Abstract: An image picked up by a detection system capable of actualizing a three-dimensional inclination is usually poor in the signal-to-noise ratio, and it is difficult to stably detect minute defects. Images that actualize a three-dimensional inclination are picked up from opposed directions. The images are subject to subtraction and addition. The images improved in signal-to-noise ratio as compared with original images are calculated. The images calculated and improved in signal-to-noise ratio respectively of a defect portion and a reference portion are compared with each other. Regions differing in comparison results are detected as defects. As a result, minute defects can be inspected stably.

Abstract: A method to solve the problem of a technique generally used to detect a defect of a semiconductor by calculating the differential image based on pattern matching, which requires that a reference image must be picked up to pick up an image of the inspection position in an area with the semiconductor pattern having no periodicity, resulting in a low throughput. The image of the inspection position is divided into local areas, each local area is matched with the local area of the image already stored and the difference between the local areas thus matched is determined to extract a defect area.

Abstract: A method of observing a specimen using a scanning electron microscope, makes it possible to shorten the time required to perform automatic focusing at the time of semiconductor defect automatic review and improves the throughput in the processing in which the specimen is observed. In the above method, the specimen is imaged at a low resolution by the scanning electron microscope to obtain an image, an area for imaging the specimen at a high resolution is specified from the image acquired at the low resolution, the specimen is imaged at a high resolution by the scanning electron microscope to determine a focus position, a focal point of the scanning electron microscope is set to the determined focus position, and a high resolution image in the specified area is acquired in a state in which the focus position has been set to the determined focus position.

Abstract: It is possible to reliably and efficiently determine whether a specimen contains viruses, bacteria, etc. and, if it does, identify their types, regardless of the observer. Furthermore, even a newly-discovered bacterium can be quickly identified by utilizing a database at a remote location. A transmission microscope system has a microscope for observing a specimen and a database which stores, for each microscopic thing (such as a virus), a name, a specimen pretreatment method and an imaging condition used when the microscopic thing is observed, captured image data, etc. An image of the specimen is captured according to a specimen pretreatment method and an imaging condition retrieved from the database using the name of a target microscopic thing as a key, and the captured image is compared with images stored in the database to identify microscopic things present in the specimen.