Systems and methods are provided for improved intra-operative micro-CT imaging of explanted tissue samples and for improved visualization of such samples. These embodiments provide for reduced scan times and the ability for radiologists to quickly receive useful scan imagery and to provide accurately-communicated recommendations to the operating surgeon. Improved scan visualization methods facilitate surgeon and radiologist interaction with the scan data, including of annotation, viewing, and reorientation to accurately reflect the orientation of imaged tissue samples relative to the body prior to explantation. Improved visualization methods include color-coded sample texturing to indicate sample orientation, color-coded tumor visualization to indicate proximity to sample margins, and intuitive methods for adjusting the location and orientation of two-dimensional visualizations relative to the sample.

A radiomic biomarker determination method and system for assessment of the risk of metabolic diseases. The method includes: obtaining abdominal & pelvic volumetric computed tomography (CT) scan from the given subject; determining the fat area to be analyzed from the CT scan, separating visceral fat using an image segmentation method, and normalizing the visceral fat area under physical scale; extracting N imaging features of the visceral fat; selecting n optimal imaging features from the N candidate features; dividing the normalized visceral fat area into multiple visceral fat blocks with equal thickness; extracting n corresponding optimal imaging features from each visceral fat block, named as block imaging features; and determining the representative visceral fat block from the candidate blocks and taking the representative visceral fat block and the (block) imaging features extracted from the representative visceral fat block as radiomic biomarkers.

In one embodiment, there is provided an apparatus for low-dimensional manifold constrained disentanglement for metal artifact reduction (MAR) in computed tomography (CT) images. The apparatus includes a patch set construction module, a manifold dimensionality module, and a training module. The patch set construction module is configured to construct a patch set based, at least in part on training data. The manifold dimensionality module is configured to determine a dimensionality of a manifold. The training module is configured to optimize a combination loss function comprising a network loss function and the manifold dimensionality. The optimizing the combination loss function includes optimizing at least one network parameter.

An image processing apparatus includes at least one processor. The processor is configured to execute region-of-interest image generation processing of generating a region-of-interest image from a projection image, which is obtained at an irradiation position closest to a position facing a detection surface of a radiation detector, among a series of projection images obtained by irradiating a breast with radiations and imaging the breast, and shape type determination processing of determining a type of a shape of a calcification image included in the region-of-interest image generated by the region-of-interest image generation processing.

In an approach to generating playlists/sequences of images, a system includes: a memory configured to store at least a first image; a one or more computer processors; one or more non-transitory computer readable storage media; and program instructions. The program instructions include: receive the first image; determine at least one characteristic associated with an object represented within the first image and an expected user input associated with the at least one characteristic; and generate a sequence definition, the sequence definition including an identifier of the first image and an identifier of the at least one characteristic, where the sequence definition is configured to cause the first image to be interactively visualized to a user via a user interface to determine if a user input matches an expected user input based on the identifier of the at least one characteristic.

A method is for providing decision-supporting data. In an embodiment, the method includes receiving photon-counting computed tomography data relating to an examination region; determining a location of a thrombus in the examination region, based on the photon-counting computed tomography data received; generating the decision-supporting data, relating to at least one of the thrombus and a vascular wall in a region of the thrombus, based on the photon-counting computed tomography data received and the location of the thrombus determined; and providing the decision-supporting data generated.

A method for improving an image quality of X-ray tomograms includes generating a low-pass filtered X-ray tomogram by applying a low-pass filter to a two-dimensional X-ray tomogram. The low-pass filter is only applied to pixels with image values lying within a predetermined image value interval. A high-pass filtered X-ray tomogram is generated by subtracting the low-pass filtered X-ray tomogram from the two-dimensional X-ray tomogram. A Radon transform image is generated by calculating a Radon transform of the high-pass filtered X-ray tomogram. A modified Radon transform image is generated by modifying values of the pixels of the Radon transform image with values lying outside a predetermined value interval. A modified high-pass filtered X-ray tomogram is generated by calculating an inverse Radon transform of the modified Radon transform image. A modified X-ray tomogram is generated by the addition of the modified high-pass filtered X-ray tomogram to the low-pass filtered X-ray tomogram.

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.

In general, an X-ray imaging apparatus according to one embodiment includes an X-ray tube, an X-ray detector, and processing circuitry. The processing circuitry is configured to obtain correction-target data that includes component deterioration resulting from a transient response of the X-ray detector, and to output, based on the obtained correction-target and a model that outputs data in which component deterioration resulting from a transient response is reduced based on an input of data that includes component deterioration resulting from a transient response, corrected data in which the component deterioration resulting from the transient response of the X-ray detector is reduced.

The present invention relates to an apparatus (10) for correcting computer tomography (“CT”) X-ray data acquired at high relative pitch, the apparatus comprising: an input unit (20); a processing unit (30); and an output unit (40). The input unit is configured to provide the processing unit with CT X-ray data of a body part of a person acquired at high relative pitch. The processing unit is configured to determine CT slice reconstruction data of the body part of the person with no or reduced high relative pitch operation reconstruction artefacts using a machine learning algorithm. The machine learning algorithm was trained on the basis of CT slice reconstruction data, and wherein the CT slice reconstruction data comprised first CT slice reconstruction data with high relative pitch reconstruction artefacts and comprised second CT slice reconstruction data with less, less severe, or no high relative pitch reconstruction artefacts. The output unit is configured to output the CT slice reconstruction data of the body part of the person.