Systems and methods are presented for providing a machine learning model for segmenting an optical coherence tomography (OCT) image. A first OCT image is obtained, and then labeled with identified boundaries associated with different tissues in the first OCT image using a graph search algorithm. Portions of the labeled first OCT image are extracted to generate a first plurality of image tiles. A second plurality of image tiles is generated by manipulating at least one image tile from the first plurality of image tiles, such as by rotating and/or flipping the at least one image tile. The machine learning model is trained using the first plurality of image tiles and the second plurality of image tiles. The trained machine learning model is used to perform segmentation in a second OCT image.

Systems and methods are presented for providing a machine learning model for segmenting an optical coherence tomography (OCT) image. A first OCT image is obtained, and then labeled with identified boundaries associated with different tissues in the first OCT image using a graph search algorithm. Portions of the labeled first OCT image are extracted to generate a first plurality of image tiles. A second plurality of image tiles is generated by manipulating at least one image tile from the first plurality of image tiles, such as by rotating and/or flipping the at least one image tile. The machine learning model is trained using the first plurality of image tiles and the second plurality of image tiles. The trained machine learning model is used to perform segmentation in a second OCT image.

This disclosure describes an apparatus and techniques for rotating image data. The rotation techniques may include fetching a strip of a block of image data from an external memory, writing the strip into a strip buffer in a first scan direction, reading a micro-block of pixels of the strip in the strip buffer in the first scan direction and writing the micro-block into a rotation buffer in the first scan direction, and rotating the micro-block of pixels by reading the micro-block of pixels in the rotation buffer in a second scan direction, the second scan direction different from the first scan direction, and writing the micro-block of pixels into a rotation memory in the second scan direction.

Methods and systems for displaying an image of a medical procedure (e.g., an intraoperative image) with additional information (e.g., data) that can augment the image of the medical procedure are provided. Augmenting the image can include overlaying data from a first image to a second image. Overlaying the data can involve determining, for a point or multiple points in the first image, a matching location or multiple matching locations in a second image. The first image and the second image can be of a patient. Determining the matching location can involve using a rotation and scale invariant geometrical relationship. The matching locations can be used as the basis for the overlay.

An apparatus adapted, including a media encoder coupled to a data interface adapted to receive a frame or portion thereof. The media encoder is adapted to iteratively subdivide each block of a plurality of blocks partitioned in a frame or portion thereof and to process a subdivided block of the plurality of blocks, during each iteration of a plurality of iterations, by selecting a rotational symmetry mask fulfilling an efficiency measure for coding said block, the rotational symmetry mask selected from a plurality of rotational symmetry masks which define a plurality of different rotational symmetries in a multidimensional space, splitting the subdivided block to two complementary portions based on the rotational symmetry mask, generating a pair of rotational symmetry blocks each having one of said two complementary portions, and computing a plurality of transform coefficients from the pair of rotational symmetry blocks.

The present invention relates to a method and apparatus for measuring rotation parameters of a spine on medical images. The method comprises: selecting a reference image and a movement image from the medical images; determining a lower spine image and an upper spine image in the reference image, and determining a lower spine image and an upper spine image in the movement image; registering the lower spine image in the movement image with the lower spine image in the reference image; correcting the upper spine image in the movement image according to output parameters of registration of the lower spine images; superposing the upper spine image in the reference image with the corrected upper spine image in the movement image to obtain a superposed image; and calculating to obtain the rotation parameters according to a position difference between the upper spine image in the reference image and the upper spine image in the movement image on the superposed image.

The present invention discloses an image processing method. The image processing method includes the following steps: (a), a to-be-processed image is corrected as a first correction image according to a first mapping relationship along a correction direction; (b) the first correction image by an angle is rotated; and (c) the rotated first correction image is corrected as a second correction image according to a second mapping relationship along the same correction direction. In embodiment, given that the to-be-processed image is deformed along two different directions, the to-be-processed image is corrected along the same correction direction, such that correction complexity could be reduced.

Methods and systems for displaying an image of a medical procedure (e.g., an intraoperative image) with additional information (e.g., data) that can augment the image of the medical procedure are provided. Augmenting the image can include overlaying data from a first image to a second image. Overlaying the data can involve determining, for a point or multiple points in the first image, a matching location or multiple matching locations in a second image. The first image and the second image can be of a patient. Determining the matching location can involve using a rotation and scale invariant geometrical relationship. The matching locations can be used as the basis for the overlay.

Techniques related to performing image registration are discussed. Such techniques include converting a source image region and a target image portion from a color image space to a semantic space and iteratively converging homography parameters using the source image region and target image portion in the semantic space by applying iterations with some homography parameters allowed to vary and others blocked from varying and subsequent iterations with all homography parameters allowed to vary.

Methods and systems for displaying an image of a medical procedure (e.g., an intraoperative image) with additional information (e.g., data) that can augment the image of the medical procedure are provided. Augmenting the image can include overlaying data from a first image to a second image. Overlaying the data can involve determining, for a point or multiple points in the first image, a matching location or multiple matching locations in a second image. The first image and the second image can be of a patient. Determining the matching location can involve using a rotation and scale invariant geometrical relationship. The matching locations can be used as the basis for the overlay.