An image processing apparatus obtains segment definition information that defines a plurality of segments obtained by dividing a human body along a body axis, and obtains a three-dimensional image including a plurality of slice images indicating cross sections of a subject. The image processing apparatus identifies, based on the segment definition information, a segment to which a cross section corresponding to at least one slice image among the slice images included in the image belongs, and calculates a coordinate value of the at least one slice image, based on the identified segment and a reference coordinate system in which a coordinate value is defined for each of the segments.

3D image data of a skeletal portion is acquired. A location of a proximal portion of a tool is calculated and a location is derived of a distal portion of the tool with respect to the skeletal portion, with respect to the 3D image data. A display indicates the derived location. First and second 2D images of the distal portion of the tool are acquired from two different poses of a 2D imaging device with respect to the subject and registered with the 3D image data. The location of the distal portion with respect to the 3D image data of the skeletal portion is determined based on the registration and an identified location of the distal portion within the 2D x-rays. Based upon the determined location, the display updates the indicated location of the distal portion. Other embodiments are also described.

An image processing apparatus includes: an obtaining unit configured to obtain three-dimensional image data and positions of a plurality of feature points in the three-dimensional image data; a designation unit configured to designate a designation point indicating a portion of interest in the three-dimensional image data; a selection unit configured to select, using information determined by a position of the designation point and the positions of the plurality of feature points, a feature point from the plurality of feature points; a generation unit configured to generate, from the three-dimensional image data, a cross section image on a plane determined based on the position of the designation point and a position of the selected feature point; and a display control unit configured to cause a display unit to display the generated cross section image.

A method for registering a three-dimensional image data record of a target region of a patient with a two-dimensional x-ray image is provided. The method includes selecting at least one rigid reference structure with an associated contour; establishing a two-dimensional gradient x-ray image and a three-dimensional gradient data record of the image data record; finding a neighborhood in the gradient x-ray image from a plurality of neighborhoods extending about test points for a plurality of contour points; establishing local two-dimensional displacement information by comparison of the contour points with the associated comparison points; establishing movement parameters of a three-dimensional movement model describing a movement of the target region between recording of the image data record and the x-ray image from the local two-dimensional displacement information; and establishing a registration transformation describing the registration by correcting the test transformation based on the movement parameters.

Mechanisms are provided for determining a measure of radiodensity of anatomical structures of interest and classifying medical imaging study data structures (studies) with regard to contrast phase. In some embodiments, this classification may be used to select/exclude slices for processing by other downstream computing systems. A subset of slices are selected from the study and, for each slice in the subset, a corresponding body part regression (BPR) score is determined. A linear regression on the BPR scores is performed and a representative slice is selected based on results of the linear regression. The representative slice is segmented and a statistical measure of a radiodensity metric for each segment in the representative slice is determined.

A method of image-guided radiation treatment is described. The method includes processing a first and second sets of image data to generate an enhanced image, wherein the enhanced image comprises a combination of the first and second sets of image data, wherein part or all of the image data comprises a target of a patient. The method also includes registering the enhanced image with another image to obtain a registration result and tracking the target using the registration result to generate tracking information. The method also includes directing treatment delivery to the target based on the tracking information obtained from the enhanced image.

The present disclosure discloses an image display method in a CT system. The method comprises: implementing CT scanning on an inspected object, to obtain CT projection data; organizing the CT projection data according to a predetermined interval; extracting basic data from the organized CT projection data by using a fixed angle as a start angle and using 360 degrees as an interval; forming a DR image based on the extracted basic data; reconstructing a three-dimensional image of the inspected object from the CT projection data; and displaying the DR image and the reconstructed three-dimensional image on a screen at the same time. In the solution, the CT data is processed to obtain DR data. After the DR data is obtained, a DR image is obtained directly using a DR data processing algorithm. This enables an image recognizer to more accurately and more rapidly inspect goods carried by a passenger using the existing experience in image recognition of the DR image.

In an X-ray diagnostic apparatus of one embodiment, an image data generator sequentially generates X-ray images based on X-rays transmitted through a subject. An image processor executes: first processing where, in response to an instruction to start correction processing, a position of a target contained in a predetermined X-ray image is obtained as a reference position; and second processing where corrected images in which positions of the target are set at the reference position are sequentially generated from newly generated X-ray images. An image data storage unit stores therein information on a reference position with respect to each set of conditions of manipulation on the subject. Upon receiving the instruction to start correction processing, the image processor executes the second processing by using information on the reference position stored in the image data storage unit, in accordance with a set of the conditions of manipulation on the subject.

An image processing apparatus according to an embodiment includes processing circuitry. The processing circuitry is configured to generate, from three-dimensional medical image data, a first cross-sectional image and a second cross-sectional image intersecting the first cross-sectional image and is configured to change display locations of the first cross-sectional image and the second cross-sectional image on a display, in conjunction with a change in an intersecting location of the first and the second cross-sectional images.

Embodiments herein disclose computer-implemented methods, computer program products and computer systems for performing a diagnostic assessment. The method may include receiving image data of a current screening image, prior screening image, current diagnostic image, or prior diagnostic image, each image corresponding to a view type. The method may include processing the image data using a trained model to determine first model output data; determining first diagnosis data associated with a first confidence score; determining patch data representing a difference between the prior screening image and the current screening image; identifying a location corresponding to the difference; and determining the patch data satisfies a condition. The method may further include receiving additional image data of diagnostic images corresponding to a second type of view, processing the additional image data to determine second model output data; and determining second diagnosis data associated with a confidence score greater than the first confidence score.