A method and system is described that includes obtaining a whole blood sample and obtaining a first light absorbance profile of the whole blood sample. Next, the whole blood sample is hemolyzed to generate a hemolyzed sample of blood and a second light absorbance profile of the hemolyzed sample of blood is obtained. The level of hemolysis in the whole blood sample is determined by comparing the first light absorbance profile and the second light absorbance profile.

A method for processing CT imaging data includes providing CT imaging data obtained at two x-ray energy levels in a first respiratory phase, preferably in an inhalation phase, of the subject and providing second CT imaging data obtained at two x-ray energy levels in a second respiratory phase, preferably in an exhalation phase, of the subject. The method may include reconstructing first regional perfusion blood volume (PBV) imaging data from the provided first CT imaging data, reconstructing second regional PBV imaging data from the provided second CT imaging data, reconstructing first virtual non-contrast (VNC) imaging data from the provided first CT imaging data, reconstructing second VNC imaging data from the provided second CT imaging data, determining a transformation function for registering the first and second reconstructed VNC imaging data, and registering the first and second reconstructed VNC imaging data by applying the transformation function.

Provided is an information processing device that includes a first information acquisition section that acquires first information on the basis of a still image in a frame corresponding to a predetermined time point, from among a plurality of images of a biological sample captured in a time-series manner, a second information acquisition section that acquires second information on the basis of an interframe change of the plurality of images in a predetermined period, and a determination section that determines an event regarding the biological sample, using the first information and the second information.

Devices, systems, methods for validating ablation results in a patient's brain are provided. In some embodiments, the method for validating ablation result in a patient's brain includes obtaining magnetic resonance (MR) data of the patient's brain, by use of a magnetic resonance imaging (MRI) device; obtaining first imaging data of the patient's brain, by use of the MRI device; extracting, by use of computing device in communication with the MRI device, first fiber tracts passing through an anatomy in the patient's brain based on the first imaging data; obtaining, by use of the MRI device, second imaging data of the patient's brain after ablation of the anatomy in the patient's brain has started; extracting second fiber tracts passing through the anatomy in the patient's brain based on the second imaging data; and outputting a graphical representation of a comparison between the first fiber tracts and the second fiber tracts.

A method of analyzing a multidimensional image tensor containing a plurality of images comprises: performing imaging scans of a subject imaging data; generating the multidimensional image tensor from the imaging data; determining a spatial basis tensor containing basis images based on the multidimensional image tensor; determining a temporal basis tensor containing basis functions for a temporal dimension based on the multidimensional image tensor; determining a core tensor that relates the spatial basis tensor to the temporal basis tensor; pre-multiplying the core tensor and the temporal basis tensor to produce a modified temporal basis tensor; storing the spatial basis tensor and the modified temporal basis tensor; and generating an image by multiplying at least (i) at least a portion of the spatial basis tensor and (ii) at least a portion of the modified temporal basis tensor.

An apparatus that can obtain a subtraction image efficiently is provided. An image processing apparatus obtains a target image constituted by a set of voxels arranged in a discretized manner; sets a search area in the target image; and obtains, in a partial area included in the search area, on the basis of at least one of a voxel value included in the partial area and an interpolated value obtained by interpolation of a voxel of the target image, at least one of a maximum and a minimum of a voxel value and an interpolated value within the search area.

A computer-implemented method and a data processing apparatus provide and apply a trained probabilistic graphical model for verifying and/or improving the consistency of labels within the scope of medical image processing. Also provided are a computer-implemented method for verifying and/or improving the consistency of labels within the scope of medical imaging processing, a data processing apparatus embodied to verify and/or improve the consistency of labels within the scope of medical image processing, and a corresponding computer program product and a computer-readable medium.

The medical information display apparatus includes an image acquisition unit that acquires a first brain image which is a brain image of a subject captured at a first time point and a second brain image captured at a second time point later in time than the first time point, a registration unit that performs registration between the first and the second brain image, an image analysis unit that extracts a first cavity region and a second cavity region from the first brain image and the second brain image, respectively, a display unit, and a display controller displays, a cavity expansion part included in a first non-cavity region, which is a region other than the first cavity region, and included in the second cavity region in a distinguishable manner from a region other than the cavity expansion part from a result of the registration between the first and second brain image.

A method of estimating lung motion includes collecting multiple ultrasound image data captured at one or more locations of a sample region of tissue. The method further includes comparing the multiple ultrasound image data and determining temporal correlation coefficients between each of the multiple ultrasound image data. The method still further includes displaying an image of the sample region of the tissue with the temporal correlation coefficients identified, thereby indicating lung motion. In further methods, the determined temporal correlation coefficients are used to determine an amount of decorrelation, which can be used to determine strain of the tissue over the sample region and to calculate lung displacements and lung shape changes representing ventilation.

A system and method to analyze image data. The image data may be used to assist in determine the presence of a feature in the image. The feature may include a bubble.