The present disclosure provides a method for automated image acquisition and imaging processing. The method may include obtaining imaging information of an object. The method may include determining, based on the imaging information, at least target device positioning information of an imaging device. The method may include causing, based on the target device positioning information of the imaging device, the imaging device to be positioned to perform the image acquisition. The method may include providing, based on the inspection information, guidance information, the guidance information being configured to guide positioning of the object. The method may also include obtaining a target image from an imaging operation by the imaging device. Further, the method may include determining a target image processing algorithm of a medical image.

A computed tomography (CT) image processing apparatus and a CT image processing method are provided. The CT image processing apparatus may generate a virtual monochromatic image (VMI) by applying a weight to each of first, second, and third images corresponding to three different energy ranges. The CT image processing apparatus may set a region of interest (ROI) on a CT image, determine a VMI at an energy level at which a CNR of the ROI is at a maximum among a plurality of VMIs, and display the determined VMI.

A multi-spectral tomography imaging system includes one or more source devices configured to direct beams of radiation in multiple spectra to a region of interest (ROI), and one or more detectors configured to receive the beams of radiation. The system includes a processor configured to cause movement in at least one of the components such that a first beam of radiation with a first spectrum is directed to the ROI for less than 360 degrees of movement of the ROI. The processor is also configured to process data detected by the one or more detectors, where the data results at least in part from the first beam of radiation with the first spectrum that is directed to the ROI for less than the 360 degrees of movement of the ROI. The processor is further configured to generate an image of the ROI based on the processed data.

An image interpretation support apparatus includes: an acquisition unit that acquires a plurality of projection images obtained by tomosynthesis imaging in which a radiation is irradiated to a breast from different irradiation angles by a radiation source and a projection image is captured at each irradiation angle by a radiation detector; a first generation unit that generates a plurality of tomographic images on each of a plurality of tomographic planes of the breast from the plurality of projection images; a second generation unit that generates a synthetic two-dimensional image from a plurality of images among the plurality of projection images and the plurality of tomographic images; a detection unit that detects an object of interest candidate region estimated to include an object of interest from the synthetic two-dimensional image; and a determination unit that determines whether or not the object of interest is included in the object of interest candidate region on the basis of the plurality of tomographic images.

Assessment of transthyretin amyloid cardiomyopathy (ATTR-CM) can be performed by calculating a cardiac pyrophosphate activity (CPA) measurement from single-photon emission computed tomography (SPECT) images. SPECT images obtained using .sup.99mTechnetium-pyrophosphate as a radiotracer can be analyzed to calculate CPA. Scan-specific thresholds for abnormal myocardial activity are identified based on left ventricular blood pool (LVBP) radiotracer counts, then radiotracer activity in regions of the myocardium with abnormal myocardial activity is determined. Finally, a CPA measurement can be calculated as a function of the mean radiotracer counts in such regions over the maximal LVBP radiotracer activity multiplied by the volume of involvement (e.g., the volume of abnormal activity). This CPA measurement can then be used as an assessment of ATTR-CM.

A method for processing breast tissue image data includes obtaining image data of a patient's breast tissue, processing the image data to generate a set of image slices, the image slices collectively depicting the patient's breast tissue; feeding image slices of the set through each of a plurality of object-recognizing modules, each of the object-recognizing modules being configured to recognize a respective type of object that may be present in the image slices; combining objects recognized by the respective object-recognizing modules to generate a synthesized image of the patient's breast tissue; and displaying the synthesized image.

A three-dimensional model for a patient fixation device that serves to immobilize at least a portion of a particular patient when capturing CT image information of that patient is accessed and then registered with the pixels that correspond to the patient fixation device in the CT image. The model can specify rules of movement for each of a plurality of structural elements that comprise the patient fixation device and that are capable of movement relative to one another. By one approach the aforementioned registration occurs on a part-by-part basis for each of the structural elements. Following registration, the CT image can be automatically segmented.

An x-ray tomography system which can generate a qualitative 3D image of a region of interest using a an x-ray source, the x-ray source configured to emit x-ray radiation at the region of interest. The x-ray radiation or the x-ray source or the relative position of the x ray source configured to be moved in a two dimensional plane. An x-ray detector including a plurality of detector elements arranged in a two dimensional plane opposite the x-ray source, the x-ray detector configured to detect x-ray radiation after attenuation by the subject and provide an indication of the detected x-rays. And a processor configured to receive the indication of the detected x-rays and resolve the detected x-ray radiation into a three dimensional image. The three dimensional image is qualitative in nature.

A system and method includes determination of a region of interest of an imaging subject, generation of a first linear attenuation coefficient map of the imaging subject, the first linear attenuation coefficient map generated to associate voxels of the region of interest of the imaging subject with greater linear attenuation coefficients than voxels of other regions of the imaging subject, attenuation-correction of a plurality of tomographic frames of the imaging subject based on the first linear attenuation coefficient map to generate a second plurality of tomographic frames, and determination of tomographic inconsistency of the second plurality of tomographic frames. Some aspects further include generation of a second linear attenuation coefficient map of the imaging subject, attenuation-correction of the plurality of tomographic frames based on the second linear attenuation coefficient map to generate a third plurality of tomographic frames, and reconstruction of a three-dimensional image based on the third plurality of tomographic frames and the determined tomographic inconsistency.

Examples of the present disclosure describe systems and methods for an auto-focus tool for multimodality image review. In aspects, an image review system may provide for the display of a set of medical images representing one or more imaging modalities. The system may also provide an auto-focus tool that may be used during the review of the set of medical images. After receiving an instruction to activate the auto-focus tool, the system may receive a selection of an ROI in at least one of the images in the set of medical images. The auto-focus tool may identify the location of the ROI within the image and use the identified ROI location to identify a corresponding area or ROI in the remaining set of medical images. The auto-focus tool may orient and display the remaining set of medical images such that the identified area or ROI is prominently displayed.