Abstract: Provided are systems and methods for determining 3D structure and 3D motion of a protein molecule from 2D or 3D particle observation images. The method including: initializing pose parameters and unknown model parameters; the parameters of the one or more flow generators; image formation including: generating one or more 3D deformation fields by inputting the latent coordinate vector into the one or more flow generators; performing a convection and projection operation; and performing CTF corruption; fitting the unknown model parameters to the experimental images by gradient-based optimization of an objective function; latent variable search for a given experimental image including: performing the image formation one or more times to generate simulated images; selecting one or more latent coordinate vectors based on similarity; updating the at least one of the unknown model parameters including: generating simulated images; evaluating the objective function; computing the gradient of the objective function.

Abstract: There is provided systems and methods for generating 3D structure estimation of at least one target from a set of 2D Cryo-electron microscope particle images. The method includes: receiving the set of 2D particle images of the target from a Cryo-electron microscope; splitting the set of particle images into at least a first half-set and a second half-set; iteratively performing: determining local resolution estimation and local filtering on at least a first half-map associated with the first half-set and a second half-map associated with the second half-set; aligning 2D particles from each of the half-sets using at least one region of the associated half-map; for each of the half-maps, generating an updated half-map using the aligned 2D particles from the associated half-set; and generating a resultant 3D map using all the half-maps.

Abstract: There is provided systems and methods for generating 3D structure estimation of at least one target from a set of 2D Cryo-electron microscope particle images. The method includes: receiving the set of 2D particle images of the target from a Cryo-electron microscope; splitting the set of particle images into at least a first half-set and a second half-set; iteratively performing: determining local resolution estimation and local filtering on at least a first half-map associated with the first half-set and a second half-map associated with the second half-set; aligning 2D particles from each of the half-sets using at least one region of the associated half-map; for each of the half-maps, generating an updated half-map using the aligned 2D particles from the associated half-set; and generating a resultant 3D map using all the half-maps.

Abstract: Disclosed herein are systems and methods for efficient 3D structure estimation from images of a transmissive object, including cryo-EM images. The method generally comprises, receiving a set of 2D images of a target specimen from an electron microscope, carrying out a reconstruction technique to determine a likely molecular structure, and outputting the estimated 3D structure of the specimen. The described reconstruction technique comprises: establishing a probabilistic model of the target structure; optimizing using stochastic optimization to determine which structure is most likely; and, optionally utilizing importance sampling to minimize computational burden.

Abstract: There is provided systems and methods for determining variability of cryo-EM protein structures from a set of cryo-electron microscope images. The method includes: performing iterative optimization, each optimization iteration including: determining the updated variability coordinates for individual images from the set of images using a current value of the variability components; determining the updated variability components for multiple images of the set of images, using the updated value of the variability coordinates, by solving a set of linear equations, the linear equations comprising a sum of weighted compositions of projection and back-projection operators, the equations are solved by arranging the equations into a block-diagonal matrix form.

Abstract: A system uses an optical sensor and an image processing apparatus to map emerged plants in a field. The optical sensor collects at least one image of a field of emerged plants. The image processing apparatus analyzes the image to detect areas of vegetation and creates a vegetation map indicative of the detected areas. The image processing element then analyzes the vegetation map to identify emerged plants within the image and creates at least map indicating locations of the emerged plants in the field. Such map may be used to make efficient crop management decisions based on the actual layout of emerged plants in the field.

Abstract: There is provided systems and methods for generating 3D structure estimation of at least one target from a set of 2D Cryo-electron microscope particle images. The method includes: receiving the set of 2D particle images of the target from a Cryo-electron microscope; splitting the set of particle images into at least a first half-set and a second half-set; iteratively performing: determining local resolution estimation and local filtering on at least a first half-map associated with the first half-set and a second half-map associated with the second half-set; aligning 2D particles from each of the half-sets using at least one region of the associated half-map; for each of the half-maps, generating an updated half-map using the aligned 2D particles from the associated half-set; and generating a resultant 3D map using all the half-maps.

Abstract: Disclosed herein are systems and methods for efficient 3D structure estimation from images of a transmissive object, including cryo-EM images. The method generally comprises, receiving a set of 2D images of a target specimen from an electron microscope, carrying out a reconstruction technique to determine a likely molecular structure, and outputting the estimated 3D structure of the specimen. The described reconstruction technique comprises: establishing a probabilistic model of the target structure; optimizing using stochastic optimization to determine which structure is most likely; and, optionally utilizing importance sampling to minimize computational burden.

Abstract: A system uses an optical sensor and an image processing apparatus to map emerged plants in a field. The optical sensor collects at least one image of a field of emerged plants. The image processing apparatus analyzes the image to detect areas of vegetation and creates a vegetation map indicative of the detected areas. The image processing element then analyzes the vegetation map to identify emerged plants within the image and creates at least map indicating locations of the emerged plants in the field. Such map may be used to make efficient crop management decisions based on the actual layout of emerged plants in the field.

Abstract: Disclosed herein are systems and methods for efficient 3D structure estimation from images of a transmissive object, including cryo-EM images. The method generally comprises, receiving a set of 2D images of a target specimen from an electron microscope, carrying out a reconstruction technique to determine a likely molecular structure, and outputting the estimated 3D structure of the specimen. The described reconstruction technique comprises: establishing a probabilistic model of the target structure; optimizing using stochastic optimization to determine which structure is most likely; and, optionally utilizing importance sampling to minimize computational burden.

Abstract: A system and a method for image alignment between at least two images to a three-dimensional model. The method including: determining a lower bound and an upper bound of an acceptable likelihood of mismatch between the at least two images; evaluating the likelihood of mismatch between the at least two images over a set of poses (r), shifts (t), or both poses (r) and shifts (t); and discarding those evaluations resulting beyond the lower bound and upper bound.

Abstract: A system and a method for image alignment between at least two images to a three-dimensional model. The method including: determining a lower bound and an upper bound of an acceptable likelihood of mismatch between the at least two images; evaluating the likelihood of mismatch between the at least two images over a set of poses (r), shifts (t), or both poses (r) and shifts (t); and discarding those evaluations resulting beyond the lower bound and upper bound.

Abstract: A system and a method for image alignment between at least two images to a three-dimensional model. The method including: determining a lower bound and an upper bound of an acceptable likelihood of mismatch between the at least two images; evaluating the likelihood of mismatch between the at least two images over a set of poses (r), shifts (t), or both poses (r) and shifts (t); and discarding those evaluations resulting beyond the lower bound and upper bound.

Abstract: A system and a method for image alignment between at least two images to a three-dimensional model. The method including: determining a lower bound and an upper bound of an acceptable likelihood of mismatch between the at least two images; evaluating the likelihood of mismatch between the at least two images over a set of poses (r), shifts (t), or both poses (r) and shifts (t); and discarding those evaluations resulting beyond the lower bound and upper bound.

Abstract: Disclosed herein are systems and methods for efficient 3D structure estimation from images of a transmissive object, including cryo-EM images. The method generally comprises, receiving a set of 2D images of a target specimen from an electron microscope, carrying out a reconstruction technique to determine a likely molecular structure, and outputting the estimated 3D structure of the specimen. The described reconstruction technique comprises: establishing a probabilistic model of the target structure; optimizing using stochastic optimization to determine which structure is most likely; and, optionally utilizing importance sampling to minimize computational burden.