Provided are an information processing apparatus, an information processing method, and a program that can suppress the generation of unnecessary images in a CT apparatus and provide images useful for diagnosis in a time-efficient manner. An information processing apparatus includes a processor, in which the processor is configured to: acquire a first image captured by a CT apparatus; execute an analysis process of the first image using a learning device; cause the CT apparatus to execute a generation process of a second image corresponding to a result of the analysis process; and display at least one of the first image, the result of the analysis process, or the second image on a display device.

A computer-implemented method of determining a value of a blood flow parameter for a vessel, is provided. The method includes: calculating from spectral attenuation data, and using a plurality of different techniques, a value of a blood flow parameter for the vessel; and providing the value of the blood flow parameter for the vessel based on the calculated values of the blood flow parameter.

A pharmaceutical hyperspectral reconstruction method based on a coded aperture snapshot spectral imaging (CASSI) system includes: collecting and processing original pharmaceutical hyperspectral images to obtain augmented pharmaceutical hyperspectral images; performing simulated spatial encoding on the augmented pharmaceutical hyperspectral images to obtain encoded measurement images; performing spectral inverse shift on the encoded measurement images, then performing inverse encoding to obtain inversely encoded three-dimensional hyperspectral images, using the augmented pharmaceutical hyperspectral images as target images, and constructing a training set and a testing set according to the inversely encoded three-dimensional hyperspectral images and the target images; constructing a deep symmetric neural reconstruction network, and training and testing the deep symmetric neural reconstruction network; and deploying a tested deep symmetric neural reconstruction network onto the CASSI system, real-time collecting pharmaceutical measurement images using the snapshot coded imaging system, and performing computational reconstruction on the pharmaceutical measurement images to obtain reconstructed three-dimensional hyperspectral images.

An image processing apparatus as an image generation apparatus includes an image generation model that has been trained in advance using a plurality of combinations of a composite two-dimensional image and a normal two-dimensional image captured by irradiating, with radiation, a breast in a state of being compressed by a compression member during tomosynthesis imaging for obtaining the composite two-dimensional image.

For visual support in a medical intervention on a hollow organ of a patient, reference data that includes a reference representation of the hollow organ is obtained, an X-ray projection image of the hollow organ is generated, and items of overlay information are determined based on the reference data. The reference data includes items of planning information relating to a location of a characteristic feature of the hollow organ in the reference representation. A reference volume is determined in the reference representation as a function of the items of planning information. A reconstruction of a volume of the patient corresponding to the reference volume is generated using a tomosynthesis method. Registration data is generated in that the reference volume is registered in relation to the reconstruction and the items of overlay information are overlaid on the X-ray projection image as a function of the registration data.

A system for inverse scattering image reconstruction using implicit neural representations (INR) is provided. The system comprises a transmitter control module, a receiver acquisition module, a random spatial sampling module, a permittivity representation module implemented using a first multilayer perceptron (MLP), an induced current representation module implemented using a second MLP, a forward simulation module, a loss computation module, and an optimization module. The system is configured to emit electromagnetic signal data toward a target object, collect scattered signal data, simulate forward electromagnetic propagation, and iteratively update the MLP parameters using loss feedback. Upon convergence, the system outputs a spatial distribution of relative permittivity values to reconstruct the internal structure of the target object.

A method for operating an X-ray facility for recording a three-dimensional (3D) image data set of a target area of a patient is provided. A recording arrangement including an X-ray detector and an X-ray source may be rotated about an axis of rotation for recording two-dimensional projection images based on the image data set. A model instance of a parameterizable patient model that is patient-specific and 3D is determined. Target area information describing the target area is determined in the model instance from default information. At least two at least partially different partial recording areas of the target area are determined from the target area information. The partial recording areas cover the target area along the axis of rotation. One projection image set is recorded for each of the partial recording areas, and the image data set is reconstructed from the projection image sets.

A method for reconstructing MR tomography images from asymmetrically acquired k-space raw data, with symmetrical and asymmetrical parts, may include reconstructing a phase image from the symmetrical k-space data, applying an iterative k-space reconstruction starting with a base image, and forming a working space via k-space transform. A weighting filter may be applied, assigning zero weight where no raw data exists, lower weight to symmetrical data, and non-zero weight to other data. A complex intermediate image is generated by image space transform of weighted k-space data, phase-corrected with the phase image, and the final result image is obtained as the real part of the phase-corrected intermediate image.

A method of reconstructing an electron microscopy image of size [Mx N] pixels of a first sample, the method implemented by a computer comprising a processor and a memory, the method comprising: providing a set of pre-learned dictionaries, including a first pre-learned dictionary including a set of p.sub.1 atoms; acquiring a sparse set of S acquired sub-images, including a first sub-image of size [ab] pixels wherein a, b[2, min {M,N}], of the first sample; and reconstructing the electron microscopy image of the first sample using the sparse set of S sub-images of the first sample and the set of pre-learned dictionaries.

A method for creating image data of an examination object using a magnetic resonance system, including: acquiring a first and at least a second set of measurement data at least of one slice, wherein during each acquisition of measurement data different acceleration factors and/or different field of view shift factors are used; and reconstructing image data based on the acquired sets of measurement data.