According to an X-ray CT apparatus and a scanning method of the present invention, in order to efficiently create an image used for diagnosis, an operator selects a desired part from a part selection GUI before main scanning by using an ROI object imitating a shape of each part, held in a storage device, and thus the ROI object can be disposed on a scanogram image, in which setting information corresponding to a part is set for the ROI object in advance, a region of interest associated with the part is set, main scanning is performed under conditions associated with the set region of interest, and an image is reconstructed on the basis of X-ray information obtained through the main scanning.

A radiographic image capturing apparatus includes: a two-dimensional array of radiation detecting elements that generate one or more electric charges in proportion to a dose of incident radiation; and a control unit that performs control, at least, to read the electric charges from the radiation detecting elements and generate image data. An image capturing mode is switchable between a controlled mode in which the radiographic image capturing apparatus is under control of an external console and a stand-alone mode in which the radiographic image capturing apparatus autonomously performs image capturing without the control of the console. When the image capturing mode is switched to the controlled mode or the stand-alone mode, the control unit changes its own process so as to meet the switched image capturing mode.

Systems, devices, and methods related to a Deep Learning Accelerator and memory are described. For example, an integrated circuit device may be configured to execute instructions with matrix operands and configured with random access memory. The random access memory is configured to store an image generated in an imaging apparatus configured to image a portion of a person, parameters of an artificial neural network, and instructions executable by the Deep Learning Accelerator to perform matrix computation to generate an output of the artificial neural network. The output can include a feature identified by the artificial neural network and a diagnosis determined by the artificial neural network to assist or guide the imaging of the portion of the person.

An assistance apparatus for assisting creation of an interpretation report obtains a set of regions of interest, which are determined as regions that were observed, of medical image data of a subject that is displayed as an interpretation target, and a set of described regions, which are regions that correspond to description of an interpretation report about the medical image data of a subject. The assistance apparatus determines consistency between the set of regions of interest and the set of described regions, and lets a display unit display a result of the determination.

The present disclosure relates to a system and method for medical imaging. An imaging device having a table may be provided. Scans of a subject located on the table at multiple table positions may be performed based on a scanning protocol, each scan covering a portion of the subject. Data may be acquired based on the scans of the subject. An image may be reconstructed based on the acquired data.

A hierarchical workflow is configured to associate examination information captured using an imaging platform with contextual metadata. The examination information may include ultrasound image data, which may be associated with annotations, measurements, pathology, body markers, and/or the like. The hierarchical workflow may comprise templates associated with respective anatomical regions, locations, volumes, and/or surfaces. A template may define configuration data to automatically adapt the imaging platform to capture imaging data in the corresponding anatomical region. The template may further include guidance information for the operator, including processing steps for capturing relevant examination information. Additional examination information may be captured and included in the hierarchical workflow.

Special displays of medical images are generated that help a radiologist better detect nodules by exploiting the inherent human visualization abilities of detection of symmetry, asymmetry, motion and relative motion. A Region of Interest (ROI) on an x-ray (mammogram, CT-scan, MRI, or other medical image) is selected and the data within the ROI is copied such that a new display now has two or more copies of the information within the ROI. This copy may contain the same relative positions as the original image, or may be a mirror image of the original data. The ROI is moved over the medical image in search of nodules. This movement can be random, under the direct control of the radiologist, systematically moved by a computer algorithm, or some combination of the above.

A method and system for incorporating voice commands into the interactive process of image segmentation. Interactive image segmentation involves a user pointing at an image; voice commands quicken this interaction by indicating the purpose and function of the pointing. Voice commands control the governing parameters of the segmentation algorithm. Voice commands guide the system to learn from the user's actions, and from the user's manual edits of the results from automatic segmentation.

Similar medical images having a predetermined similarity to a region of interest in a medical image to be interpreted are received from a case search system. A display screen on which the received similar medical images are displayed is displayed on a display. The display screen includes display frames within which similar medical images are displayed. In response to an instruction for enlarging the similar medical images, corresponding regions of interest in the similar medical images are enlarged and displayed with the sizes of the display frames maintained unchanged on the display screen. In response to an instruction for causing a selected similar medical image among the enlarged and displayed similar medical images to move within a corresponding display frame, the other unselected similar medical image(s) is caused to move within a corresponding display frame synchronously with the movement of the selected similar medical image in the same movement direction.

Systems and methods are disclosed for predicting healthy lumen radius and calculating a vessel lumen narrowing score. One method of identifying a lumen diameter of a patient's vasculature includes: receiving a data set including one or more lumen segmentations of known healthy vessel segments of a plurality of individuals; extracting one or more lumen features for each of the vessel segments; receiving a lumen segmentation of a patient's vasculature; determining a section of the patient's vasculature; and determining a healthy lumen diameter of the section of the patient's vasculature using the extracted one or more features for each of the known healthy vessel segments of the plurality of individuals.