The brain appears to have organized cardiac frequency angiographic phenomena with such coherence as to qualify as vascular pulse waves. Separate arterial and venous vascular pulse waves may be resolved. This disclosure states the method of extracting a spatiotemporal reconstruction of the cardiac frequency phenomena present in an angiogram obtained at faster than cardiac frequency. A wavelet transform is applied to each of the pixel-wise time signals of the angiogram. If there is motion alias then instead a high frequency resolution wavelet transform of the overall angiographic time intensity curve is cross-correlated to high temporal resolution wavelet transforms of the pixel-wise time signals. The result is filtered for cardiac wavelet scale then pixel-wise inverse wavelet transformed. This gives a complex-valued spatiotemporal grid of cardiac frequency angiographic phenomena. It may be rendered with a brightness-hue color model or subjected to further analysis.

A method may include acquiring MR signals by an MR scanner and generating image data in a k-space according to the MR signals. The method may also include classifying the image data into a plurality of phases. Each of the plurality of phases may have a first count of spokes. A spoke may be defined by a trajectory for filling the k-space. The method may also include classifying the plurality of phases of the image data into a plurality of groups and determining reference images based on the plurality of groups. Each of the reference images may correspond to the at least one of the phases of the image data. The method may further include reconstructing an image sequence based on the reference images and the plurality of phases of the image data.

Topological evolution of a lesion within a time series of medical imagery is provided. In various embodiments, a time series of medical images is read. Each of the images depicts a subject anatomy and a lesion. The lesion has a size and a contour within each of the medical images. At least one anatomical label is read for the subject anatomy within each of the plurality of images. Based upon the contour of the lesion within each of the medical images and based on the at least one anatomical label, a further contour of the lesion is predicted outside of the time series.

A method of grouping detection events in an imaging apparatus is described herein. The detection events can include primary detection events and secondary scattered events, which are frequently discarded due to the secondary scattered events, thus reducing sensitivity of the dataset for eventual image reconstruction. The method includes cell modules cascaded with identical parametrized cells, in a pipeline fashion, having the last cell in the chain circle back to the first cell. A rotating data pointer indicates the location of the first entry in the cell pipeline. The described method enables the grouping of multiple samples of detector data in real time with no loss of information, based on a time and location of the detected event. The method can be implemented in an FPGA as a hardware-based real time process.

Data is computed in order to visualize the velocity of blood fluid flowing through a blood vessel at a fundus. An image processing method includes a step of performing registration of each frame in a moving image configured by plural frames of an imaged fundus, and a step of computing visualization data enabling visualization of a state of blood fluid flowing through a blood vessel at the fundus based on a pixel value in each of the registered frames.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for jointly training an encoder neural network and a decoder neural network. In one aspect, a method comprises: updating current values of a set of encoder parameters and current values of a set of decoder parameters using gradients of a reconstruction loss function that measures an error in a reconstruction of multi-modal data from a training example, wherein: the reconstruction loss function comprises a plurality of scaling factors that each scale a respective term in the reconstruction loss function that measures an error in the reconstruction of a corresponding proper subset of feature dimensions of the multi-modal data from the training example.

A method of detecting one or more change in an eye and a method diagnosing or providing an indication of an eye disease or eye condition or a neurodegenerative disease or condition, or a predisposition thereto are disclosed. The method of detection comprises comparing an image of the eye with at least one asynchronous image of the eye to thereby detect the one or more change in the eye wherein the change comprises a darkening or lightening in pigment of the Retinal Pigmented Epithelium (RPE) in the macula. The method of diagnosing or providing an indication of an eye disease or eye condition or a neurodegenerative disease or condition or a predisposition thereto comprises the same comparison and when the change is detected, providing a diagnosis of, indication of or to an eye disease or eye condition or a neurodegenerative disease or condition or a predisposition thereto.

In various exemplary embodiments systems and methods for determining an efficacy of a cosmetic skin treatment are provided. In an exemplary embodiment, a system for determining an efficacy of a cosmetic skin treatment comprises: a sensor configured to determine a skin ageing information item of a user and a memory configured to store the skin ageing information item of the user determined by the sensor. A processor is configured to determine an objective skin treatment success of the user on the basis of a comparison of the skin ageing information item of the user measured by the sensor with a stored skin ageing information item stored in the memory.

A device receives a prior image associated with an anatomy of interest, and receives measurements associated with the anatomy of interest. The device processes the prior image and the measurements, with a reconstruction of difference technique, to generate a difference image associated with the anatomy of interest, wherein the difference image indicates one or more differences between the prior image and the measurements. The device generates, based on the difference image and the prior image, a final image associated with the anatomy of interest, and provides, for display, the final image associated with the anatomy of interest.

An image processing apparatus obtains segment definition information that defines a plurality of segments obtained by dividing a human body along a body axis, and obtains a three-dimensional image including a plurality of slice images indicating cross sections of a subject. The image processing apparatus identifies, based on the segment definition information, a segment to which a cross section corresponding to at least one slice image among the slice images included in the image belongs, and calculates a coordinate value of the at least one slice image, based on the identified segment and a reference coordinate system in which a coordinate value is defined for each of the segments.