One or more example embodiments of the present invention relates to a computer-implemented method for providing an outline of a lesion in digital breast tomosynthesis includes receiving input data, wherein the input data comprises a reconstructed tomosynthesis volume dataset based on projection recordings, a virtual target marker within a lesion being in the tomosynthesis volume dataset; applying a trained function to at least a part of the tomosynthesis volume dataset to establish an outline enclosing the lesion, the part of the tomosynthesis volume dataset corresponding to a region surrounding the virtual target marker in the tomosynthesis volume dataset; and providing output data, wherein the output data is an outline of a two-dimensional area or a three-dimensional volume surrounding the target marker.

An approach for improving determining a significant slice associated with a tumor from a volume of medical images is disclosed. The approach is based on the annotation of tumor range and the slice index in which the tumor appears to have the largest area. The approach infer a tumor growth classifier on sliding window of the volume slices and creates a discrete integral function out of the classifier predictions. The approach applies post processing on the discrete integral function which can include a smoothing function and a bias correction. The approach selects the slice index of maximum value from the post processing step.

Wavelet transformation is performed on first image data and second image data until a decomposition level becomes a decomposition level based on synthesis control data or the like, and first wavelet coefficient data and second wavelet coefficient data are thereby generated. An ROI coefficient related to an ROI and a non-ROI coefficient in the first wavelet coefficient data are determined on the basis of mask data and the ROI coefficient in the first wavelet coefficient data and a wavelet coefficient in the second wavelet coefficient data are synthesized with each other, and synthesized coefficient data are thereby generated. Inverse wavelet transformation is performed on the synthesized coefficient data until a decomposition level becomes a predetermined end level, and synthetic image data are thereby generated.

Methods and systems disclosed herein relate generally to processing images to estimate whether at least part of a tumor is represented in the images. A computer-implemented method includes accessing an image of at least part of a biological structure of a particular subject, processing the image using a segmentation algorithm to extract a plurality of image objects depicted in the image, determining one or more structural characteristics associated with an image object of the plurality of image objects, processing the one or more structural characteristics using a trained machine-learning model to generate estimation data corresponding to an estimation of whether the image object corresponds to a lesion or tumor associated with the biological structure, and outputting the estimation data for the particular subject.

A system and method for reviewing a tomosynthesis image data set comprising volumetric image data of a breast, the method comprising, in one embodiment, causing an image or a series of images from the data set to be displayed on a display monitor and selecting or indicating through a user interface an object or region of interest in a presently displayed image of the data set, thereby causing an image from the data set having a best focus measure of the user selected or indicated object or region of interest to be automatically displayed on the display monitor.

An image processing apparatus includes at least one processor. The processor is configured to execute calcification image detection processing of detecting a calcification image based on a plurality of tomographic images obtained from a series of a plurality of projection images obtained by tomosynthesis imaging of a breast, region-of-interest image group generation processing of generating a region-of-interest image group by cutting out, as a region-of-interest image, a region including the calcification image detected by the calcification image detection processing from each of the plurality of projection images, variance value calculation processing of calculating a variance value of feature amounts of each of the region-of-interest images included in the region-of-interest image group, and shape type determination processing of determining a type of a shape of the calcification image based on the variance value calculated by the variance value calculation processing.

According to one embodiment, a medical image processing apparatus includes processing circuitry. The processing circuitry designates a region of interest in a first tomogram among multiple tomograms which are based on tomosynthesis imaging performed with a subject compressed in a first direction. The processing circuitry specifies a second tomogram corresponding to the region of interest from among multiple tomograms which are based on tomosynthesis imaging performed with the subject compressed in a second direction different from the first direction.

Digital Breast Tomosynthesis allows for the acquisition of volumetric mammography images. The present invention allows for novel ways of viewing such images to detect microcalcifications and obstructions. In an embodiment a method for displaying volumetric images comprises computing a projection image using a viewing direction, displaying the projection image and then varying the projection image by varying the viewing direction. The viewing direction can be varied based on a periodic continuous mathematical function. A graphics processing unit can be used to compute the projection image and bricking can be used to accelerate the computation of the projection images.

A plurality of radiographic images are captured of a portion of a patient in periodic motion, such as cardiac images (heartbeat motion) or lungs (breathing motion). A first subset of the captured radiographic images are identified as having a common first capture time relative to a phase of the periodic motion. A first 3D image is reconstructed using the first subset of captured radiographic images. Additional subsets of the radiographic images are processed similarly based on their common capture time relative to the phase of the periodic motion.

A medical image processing apparatus and a medical image processing method are provided which are capable of clearly presenting a distal end of a medical device in a tomosynthesis image of an object under examination into which the medical device is inserted. The medical image processing apparatus handles a tomosynthesis image generated using a plurality of projection images obtained by imaging an object under examination in an angle range of less than 180 degrees, and includes: a storage section for pre-storing blur data at individual imaging space coordinates; and a correction section for correcting the tomosynthesis image using the blur data.