The invention in its various embodiments relates to a method of providing surgical guidance and targeting in robotic surgery systems. The method utilizes data from a navigation system in tandem with 2-dimensional (2D) intra-operative imaging data. 2D intra-operative image data is superimposed with a pre-operative 3-dimensional (3D) image and surgery plans made in the pre-operative image coordinate system. The superimposition augments real-time intraoperative navigation for achieving image guided surgery in robotic surgery systems. Also, a robotic surgery system that incorporates the method of providing surgical guidance and targeting is disclosed. The advantages include minimizing radiation exposure to a patient by avoiding intra-operative volumetric imaging, mobility of tools, imager and robot in and out of the operating space without the need for re-calibration, and relaxing the need for repeating precise imaging positions.

A novel proton imaging system incorporates positron emission detections to enhance proton therapy treatment preparation and procedural efficiencies while reducing operational costs associated with proton therapy. In one case, the novel proton imaging system incorporating a positron emission tomography (PET) module enables rapid on-the-fly in vivo range verification for proton therapy using position information from short-lived positron emitters produced during treatment. This unique in vivo range verification method produces more streamlined, accurate, and cost-effective results relative to conventional proton imaging systems. In another case, the novel proton imaging system incorporating the PET module provides a unique combinatory PET/pCT (proton computer tomography) scanning that creates more accurate maps for proton therapy planning for metabolically-active tumors. This proton imaging system also utilizes a novel concept of “virtual protons” originating from in vivo range verification measurements that mimic proton particle's characteristics for more accurate proton computer tomography (pCT) or computer tomography (CT).

A system and method for image correction is provided. The method includes: receiving an original image; pre-correcting the original image; generating correction data based on the original image and the pre-corrected image; weighting the original image and the pre-corrected image based on the correction data; and generating a corrected image based on the weighting.

Methods and systems for image processing are provided. A target image may be acquired, wherein the target image may include a plurality of elements, an element of which may correspond to a pixel or a voxel. The target image may be decomposed into at least one layer, wherein the at least one layer may include a low frequency sub-image and a high frequency sub-image. The at least one layer may be transformed. The transformed layer may be reconstructed into a composite image.

A method and apparatus is provided to predict a regularization parameter for regularized iterative reconstruction of radiation detection data (e.g., computed tomography (CT) data or positron-emission tomography (PET) data) to generate a reconstructed image having specified statistical properties. The predicted regularization parameter is determined using a root-finding method performed on a transcendental objective function. The objective function is calculated using a three-dimensional Fourier transforms of an approximation to a shift invariant Hessian matrix and of matrix products between the forward-projection and back projection matrices of the system model and various (statistical) weight matrices. The specified statistical properties can include the standard deviation within a region of interest, a local spatial resolution, a low-contrast-detectability metric, etc. In addition to the specified statistical properties, the prediction of the regularization parameter accounts for the statistical properties of the radiation detection data, the display field of view, and the system model.

Systems and methods are provided for reprojection and back projection of objects of interest via homographic transforms, and particularly one-dimensional homographic transforms. In one example, a method may include acquiring imaging data corresponding to a plurality of divergent X-rays, assigning a single functional form to the plurality of divergent X-rays, determining, via a homographic transform, weights of interaction between a plurality of distribution samples and a plurality of X-ray detector bins based on the single functional form, and reconstructing an image based on the weights of interaction.

In a method and apparatus, magnetic resonance angiography images of an examination volume of a patient are obtained using time-of-flight angiography in a magnetic resonance scanner. By continuous recording, a number of two-dimensional slice images covering the examination volume along an axial direction are acquired in a slice-by-slice layer-wise, such as with overlapping. The slice images are divided into groups of, in each case, a predetermined number of consecutive slice images in the axial direction. A maximum intensity projection image is determined for each group, and the angiography images are determined as the maximum intensity projection images and/or dependent on the maximum intensity projection images.

A method for volumetric image reconstruction of data collected from a plurality of radiation beams emitted from axially offset positions includes receiving projection data from at least two radiation beams emitted from axially offset positions, defining a first boundary between a first region irradiated only by a first beam of the at least two radiation beams and a second region irradiated by both the first beam and a second beam of the at least two radiation beams, defining a weighting function as a function of the first boundary, and reconstructing a volumetric image from the data that is weighted with the weighting function. Each beam moves on a circular trajectory and radiates at a plurality of view angles over the circular trajectory.

According to various embodiments, the present disclosure provides a collimator for medical imaging. The collimator includes a perforated plate with a top surface and a bottom surface and holes distributed on the perforated plate. The holes are arranged in a plurality of groups. The plurality of groups forms a first coded aperture pattern and the holes in each of the plurality of groups form a second coded aperture pattern.

A method for dark-field imaging includes acquiring dark-field image projections of an object with an imaging apparatus that includes an x-ray interferometer, applying a pressure wave having a predetermined frequency to the object for each acquired projection, wherein the predetermined frequency is different for each projection, and processing the acquired projections, thereby generating a 3D image of the object. In other words, the method corresponds to acoustically modulated X-ray dark field tomography. An imaging system (400) includes a scanner (401) configured for dark-field imaging, the scanner including: a source/detector pair (402/408) and a subject support (416), a pressure wave generator (420) configured to generate and transmit pressure waves having predetermined frequencies, and a console (424) that controls the scanner and the pressure wave generator to acquire at least two dark-field projection of an object with different pressure waves having different frequencies applied to the object.