A method, apparatus and computer program for generating a sub-volume within a 3D dataset in a consistent, repeatable fashion. To accomplish this, geometric object(s) (e.g., 2D planes) are placed at precise anatomic landmarks with precise sizes and orientations. This serves to divide the 3D object into multiple parts (e.g., a first portion of the 3D volume has a first set of voxels and a second portion of the 3D volume has a second set of voxels). This process continues as multiple additional geometric objects are placed so that certain features of the 3D dataset can be extracted (i.e., shown with the best viewing settings). This process when used in conjunction with a radiologist's checklist enables efficient volume-by-volume viewing.

The present invention relates to an ultrasound imaging system comprising: an image processor configured to receive at least one set of volume data resulting from a three-dimensional ultrasound scan of a body and to provide corresponding display data, an anatomy detector configured to detect a position and orientation of an anatomical object of interest within the at least one set of volume data, a slice generator for generating a plurality of two-dimensional slices from the at least one set of volume data, wherein said slice generator is configured to define respective slice locations based on the results of the anatomy detector for the anatomical object of interest so as to obtain a set of two-dimensional standard views of the anatomical object of interest, wherein the slice generator is further configured to define for each two-dimensional standard view which anatomical features of the anatomical object of interest are expected to be contained, and an evaluation unit for evaluating a quality factor for each of the generated plurality of two-dimensional slices by comparing each of the slices with the anatomical features expected for the respective two-dimensional standard view.

A computer-implemented method for visualization of an elongated anatomical structure (20), for example of a fetal spine using ultrasound is provided. The method comprising the steps of: receiving a plurality of 3D ultrasound image volumes, each image volume depicting at least a portion of an elongated anatomical structure (20); on each 3D ultrasound image volume, automatically or semi-automatically fitting a parametric curve (30) to the depicted portion of the elongated anatomical structure, the parametric curve being defined by curve parameters; reformatting each 3D ultrasound image volume by applying a transformation which straightens the parametric curve along at least one axis, so as to generate a plurality of reformatted image volumes and reformatted parametric curves (32, 34); registering the reformatted image volumes with one another by determining the joining point of their respective parametric curves; and fusing the reformatted image volumes with one another to yield a fused image depicting the whole elongated anatomical structure or a larger portion thereof than the 3D ultrasound image volumes.

The invention provides a method for refining a mapped surface mesh of a cardiac chamber. The method includes obtaining a mapped surface mesh of the cardiac chamber anatomy, wherein the mapped surface mesh comprises a central region representing a cardiac chamber and an outer region representing a peripheral cardiac structure connected to the cardiac chamber, and wherein the mapped surface mesh comprises a first view of an anatomical landmark within the cardiac chamber, and obtaining image data of a cardiac chamber anatomy of a subject. The central region of the mapped surface mesh is deformed based on a first segmentation algorithm configured according to one or more predetermined shape- constraints and the outer region of the mapped surface mesh is deformed based on a second segmentation algorithm configured according to the image data, thereby generating a deformed outer region. The deformed central region and the deformed outer region are then combined, thereby generating a refined mapped surface mesh.

A method of analyzing an image of a volume of tissue to determine a risk of developing breast cancer using a volume averaged sound speed within the volume. A method of determining a response to a treatment plan by determining a volume and a volume averaged sound speed of a region of interest within a volume of breast tissue and generating a combined metric from the volume and the volume averaged sound speed over the plurality of instances of time. A method of analyzing an image of a volume of tissue of a breast by applying a spatial filter to at least one ultrasound tomography image at the computing system and generating a stiffness map from the at least one ultrasound tomography image.

According to one embodiment, an ultrasonic diagnosis apparatus includes processing circuitry. The processing circuitry generates three-dimensional data based on an echo reflection intensity acquired through a probe, acquires a plurality of parameters including base color parameters, and the three-dimensional data, and generates a rendering image of the three-dimensional data using a value of color attenuation taking account of propagation of light based on the echo reflection intensity and using the base color parameters.

Various methods and systems are provided for a medical imaging system. In one embodiment, a method includes acquiring a series of medical images of a lung, identifying a pleural line in each medical image of the series, evaluating the pleural line for irregularities in each medical image of the series, and outputting an annotated version of each medical image of the series, the annotated version including visual markers for healthy pleura and irregular pleura. In this way, an operator of the medical imaging system may be alerted to pleural irregularities during a scan.

To register a position and an angle of a scanning surface of an ultrasound probe easily and accurately. A phantom including two or more wires stretched in a non-parallel manner is disposed in a real space in which a position detection sensor is disposed. An ultrasound probe, to which a probe position detection marker is attached, is moved on the phantom in a parallel manner while keeping an orientation of a main plane of the ultrasound probe constant. Two or more ultrasound images of the phantom are acquired while detecting a position of the probe position detection marker in the real space with the position detection sensor. Positions of cross-sectional images of the two or more wires included in each of the two or more ultrasound images are obtained. A relation between the position of the probe position detection marker in the real space and orientations and positions of the captured ultrasound images in the real space is calculated based on a relation between the obtained positions of the cross-sectional images. The calculated relation as probe coordinate transformation information is registered in a storage unit.

For three-dimensional segmentation from two-dimensional intracardiac echocardiography imaging, the three-dimension segmentation is output by a machine-learnt multi-task generator. Rather than the brute force approach of training the generator from 2D ICE images to output a 2D segmentation, the generator is trained from 3D information, such as a sparse ICE volume assembled from the 2D ICE images. Where sufficient ground truth data is not available, computed tomography or magnetic resonance data may be used as the ground truth for the sample sparse ICE volumes. The generator is trained to output both the 3D segmentation and a complete volume (i.e., more voxels represented than in the sparse ICE volume). The 3D segmentation may be further used to project to 2D as an input with an ICE image to another network trained to output a 2D segmentation for the ICE image. Display of the 3D segmentation and/or 2D segmentation may guide ablation of tissue in the patient.

A method of displaying an area of interest within a surgical site includes modeling a patient's lungs and identifying a location of an area of interest within the model of the patient's lungs. The topography of the surface of the patient's lungs is determined using an endoscope having a first camera, a light source, and a structured light pattern source. Real-time images of the patient's lungs are displayed on a monitor and the real-time images are registered to the model of the patient's lungs using the determined topography of the patient's lungs. A marker indicative of the location of the area of interest is superimposed over the real-time images of the patient's lungs. If the marker falls outside of the field-of view of the endoscope, an arrow is superimposed over the real-time images to indicate the direction in which the marker is located relative to the field of view.