Imaging systems and methods are provided, which involve acquiring static volume data using a first imaging technique; segmenting the static volume data to generate a static segmentation; annotating the static segmentation with at least one annotation; acquiring initial dynamic volume data using a second imaging technique different to the first imaging technique; segmenting the initial dynamic volume data to generate a plurality of dynamic segmentations; comparing the static segmentation to each one of the plurality of dynamic segmentations and determining, using the comparisons, a single dynamic segmentation that most closely corresponds to the static segmentation; storing the corresponding single dynamic segmentation in the memory as a reference segmentation; acquiring subsequent dynamic volume data; segmenting the subsequent dynamic volume data to generate at least one subsequent dynamic segmentation; determining a difference between the reference segmentation and the subsequent dynamic segmentation; updating the at least one annotation using the determined difference; and displaying the at least one updated annotation together with the subsequent dynamic volume data.

The invention related to a method and a device for displaying an object, in particular biological tissue. Said method having the following steps: a) generating a first image of at least one sub-region of the object using a first device; b) generating a second image of at least one sub-region of the object using a second device; c) ascertaining first coordinates of at least some image points of the second image in a first coordinate system; d) ascertaining second coordinates of the image points of the second image by projecting the first coordinates in a second coordinate system which is different from the first coordinate system and which is assigned to the first device; and e) generating a combined image of the object from the first and the second image using the ascertained second coordinates of the image points of the second image.

Disclosed is a computer-implemented method of determining a correspondence between a region of interest as it appears in a first digital medical patient image and as it appears in a second digital medical image. The correspondence is determined by calculating the ratio of overlap of the region of interest with a data object defining an anatomical body part in the first image and the second image and determining whether the larger of the two ratios exceeds a threshold. If the threshold is exceeded, the method assumes that the appearances in the two images describe the same region of interest.

Methods and apparatus for treating a patient. The method includes acquiring a plurality of radio frequency (RF) signals with an ultrasound transducer, each RF signal representing one or more return echoes from a scan line of a pulse-mode echo ultrasound scan. A position of the ultrasound transducer corresponding to each of the acquired RF signals is determined, and a plurality of contour lines generated from the plurality of RF signals. The method estimates a 3-D shape and position of an anatomical feature, such as a joint of patient based on the generated contour lines and corresponding ultrasound transducer positions. An apparatus, or computer includes a processor and a memory with instructions that, when executed by the processor, perform the aforementioned method.

A method is provided for measuring or estimating stress distributions on heart valve leaflets by obtaining three-dimensional images of the heart valve leaflets, segmenting the heart valve leaflets in the three-dimensional images by capturing locally varying thicknesses of the heart valve leaflets in three-dimensional image data to generate an image-derived patient-specific model of the heart valve leaflets, and applying the image-derived patient-specific model of the heart valve leaflets to a finite element analysis (FEA) algorithm to estimate stresses on the heart valve leaflets. The images of the heart valve leaflets may be obtained using real-time 3D transesophageal echocardiography (rt-3DTEE). Volumetric images of the mitral valve at mid-systole may be analyzed by user-initialized segmentation and 3D deformable modeling with continuous medial representation to obtain, a compact representation of shape. The regional leaflet stress distributions may be predicted in normal and diseased (regurgitant) mitral valves using the techniques of the invention.

To simulate a 3D image of a subsurface below a surface, the system having a memory device for storing an instruction, a processor in communication with the memory device configured to execute the instruction, and a subsurface image capture module in communication with the processor, the subsurface image capture module having one or more wave generating device and one or more sensor affixed to a vehicle to capture a series of digital image datasets of the subsurface with a coordinate reference data, wherein the processor executes an instruction to generate a digital model of the series of digital image datasets of the subsurface while maintaining the coordinate reference data, wherein the processor executes an instruction to determine a depth map of the digital model, and wherein the processor executes an instruction to identify a key subject point in the digital model, where subsurface includes an internal biology, below ground, underwater.

An ultrasound diagnosis apparatus includes processing circuitry. The processing circuitry obtains three-dimensional medical image data, taken by using an ultrasound probe, of a region including a heart valve of a patient and a catheter inserted into a heart chamber of the patient. The processing circuitry determines an advancing direction of a tip end part of the catheter by obtaining information on a position and a posture of the tip end part included in the three-dimensional medical image data, by using at least one selected from shape information indicating the shape of the tip end part and reflection characteristic information indicating ultrasound reflection characteristics of the tip end part. The processing circuitry generates a display image from the three-dimensional medical image data in accordance with the position and the advancing direction of the tip end part. The processing circuitry causes the display image to be displayed.

An image processing system according to an embodiment includes a first aligning unit, an output unit, a second aligning unit, and a display unit. The first aligning unit aligns first three-dimensional medical image data with second three-dimensional medical image data. The output unit outputs, as output data, data obtained by adding alignment information to the first three-dimensional medical image data and to the second three-dimensional medical image data or synthetic data obtained by aligning and synthesizing the first three-dimensional medical image data with the second three-dimensional medical image data. The second aligning unit receives the output data and aligns the second three-dimensional medical image data with one or a plurality of pieces of X-ray image data. The display unit displays image data obtained by aligning the first three-dimensional medical image data with X-ray image data based on an alignment result.

Embodiments for aligning a volume to a standard alignment are provided. One example method of aligning a volume constructed from captured image data to a standard orientation includes determining an orientation and a scale of the volume based on a comparison of a volume model representing the volume to captured image data of the volume over time and adjusting the volume according to the determined orientation and scale.

Disclosed are a super-resolution reconstruction method and an apparatus for three-dimensional contrast-enhanced ultrasound images, a computer readable storage medium and an electronic device. The method includes: performing at least one thinning operation on a first three-dimensional local image sequence, the thinning operation being configured to enhance motion trajectories of microbubbles; and performing an image reconstruction operation based on the first three-dimensional local image sequence subjected to the at least one thinning operation, so as to generate three-dimensional super-resolution images. The super-resolution reconstruction method for the three-dimensional contrast-enhanced ultrasound images, by means of performing thinning operations (for example, respectively performing a first thinning operation and a second thinning operation) on the first three-dimensional local image sequence, highlights motion trajectories of microbubbles, thereby improving a signal-to-noise ratio of an image. Compared with a prior method, the reconstruction efficiency and precision of the three-dimensional super-resolution imaging are improved.