A system and a method for measuring of parameter values of semiconductor objects within wafers with increased throughput include using a modified machine learning algorithm to extract measurement results from instances of semiconductor objects. A training method for training the modified machine learning algorithm includes reducing a user interaction. The method can be more flexible and robust and can involve less user interaction than conventional methods. The system and method can be used for quantitative metrology of integrated circuits within semiconductor wafers.

In the present invention, at the time of measuring, using a CD-SEM, a length of a resist that shrinks when irradiated with an electron beam, in order to highly accurately estimate a shape and dimensions of the resist before shrink, a shrink database with respect to various patterns is previously prepared, said shrink database containing cross-sectional shape data obtained prior to electron beam irradiation, a cross-sectional shape data group and a CD-SEM image data group, which are obtained under various electron beam irradiation conditions, and models based on such data and data groups, and a CD-SEM image of a resist pattern to be measured is obtained (S102), then, the CD-SEM image and data in the shrink database are compared with each other (S103), and the shape and dimensions of the pattern before the shrink are estimated and outputted (S104).

A method, a non-transitory computer readable medium and a three-dimensional evaluation system for providing three dimensional information regarding structural elements of a specimen. The method can include illuminating the structural elements with electron beams of different incidence angles, where the electron beams pass through the structural elements and the structural elements are of nanometric dimensions; detecting forward scattered electrons that are scattered from the structural elements to provide detected forward scattered electrons; and generating the three dimensional information regarding structural elements based at least on the detected forward scattered electrons.

Apparatuses and methods for aligning lamella to charged particle beams based on a volume reconstruction are disclosed herein. An example method at least includes forming a reconstructed volume of a portion of a sample, the sample including a plurality of structures, and the reconstructed volume including a portion of the plurality of structures, performing, over a range of angles, a mathematical transform on each plane of a plurality of planes of the reconstructed volume, and based on the mathematical transform on each plane of the plurality of planes, determining a target orientation of the sample within the range of angles, wherein the target orientation aligns the plurality of structures parallel to an optical axis of a charged particle beam.

The system described herein relates to a method for generating a composite image of an object using, for example, a particle beam device such as an electron beam device and/or an ion beam device. A composite image is generated by relatively arranging a first sub image to a second sub image such that the first sub image overlaps the second sub image in the entire common region, a calculated first image position of a first marking in the first sub image is arranged on the first image position of the first marking in the second sub image, and a calculated second image position of a second marking in the first sub image is arranged on the second image position of the second marking in the second sub image.

A method of investigating a specimen using charged-particle microscopy, comprising the following steps: (a) On a surface of the specimen, selecting a virtual sampling grid extending in an XY plane and comprising grid nodes to be impinged upon by a charged-particle probing beam during a two-dimensional scan of said surface; (b) Selecting a landing energy E.sub.i for said probing beam, with an associated nominal Z penetration depth d.sub.i below said surface; (c) At each of said nodes, irradiating the specimen with said probing beam and detecting output radiation emanating from the specimen in response thereto, thereby generating a scan image I.sub.i; (d) Repeating steps (b) and (c) for a series {E.sub.i} of different landing energies, corresponding to an associated series {d.sub.i} of different penetration depths, further comprising the following steps: (e) Pre-selecting an initial energy increment ΔE.sub.i by which E.sub.i is to be altered after a first iteration of steps (b) and (c); (f) Associating energy increment ΔE.sub.i with a corresponding depth increment Δd in the value of d.sub.i; (g) Selecting said sampling grid to have a substantially equal node pitch p in X and Y, which pitch p is matched to the value of Δd so as to produce a substantially cubic sampling voxel; (h) Selecting subsequent energy values in the series {E.sub.i} so as to maintain a substantially constant depth increment Δd between consecutive members of the series {d.sub.i}, within the bounds of selected minimum and maximum landing energies E.sub.min and E.sub.max, respectively.

A sample holder retains a sample and can continuously rotate the sample in a single direction while the sample is exposed to a charged particle beam (CPB) or other radiation source. Typically, the CPB is strobed to produce a series of CPB images at random or arbitrary angles of rotation. The sample holder can rotate more than one complete revolution of the sample. The CPB images are used in tomographic reconstruction, and in some cases, relative rotation angles are used in the reconstruction, without input of an absolute rotation angle.

Provided is a method of computing precise disparity using a stereo matching method based on developed census transform with an adaptive support weight method in area based stereo matching. The method includes a step of setting an adaptive support weight window centered on a specific point of a left image and setting adaptive support weight windows with the same size with respect to one point positioned within a maximum disparity prediction value about a specific point of the left image in a right image.

The present invention relates to a method, an apparatus and a computer program for analyzing and/or processing of a mask for lithography, in particular a mask for EUV lithography.

A method for analyzing and/or processing of a mask for lithography, in particular a mask for EUV lithography, is described, which method comprises the following steps: 1a.) generating at least one particle beam vortex; and 1b.) using the particle beam vortex for analyzing and/or processing of the mask.

Disclosed herein is a method for cross-section processing and observation, and apparatus therefore, the method including: performing a position information obtaining process of observing the entirety of a sample by using an optical microscope or an electron microscope, and of obtaining three-dimensional position coordinate information of a particular observation target object included in the sample; performing a cross-section processing process of irradiating a particular region in which the object is present by using a focused ion beam based on the information, and of exposing a cross section of the region; performing a cross-section image obtaining process of irradiating the cross section by using an electron beam, and of obtaining a cross-section image of a predetermined size region including the object; and performing a three-dimensional image obtaining process of repeating the cross-section processing process and the cross-section image obtaining process at predetermined intervals in a predetermined direction, and of obtaining a three-dimensional image from obtained multiple cross-section images.