A method for determining respiratory induced blood mass change from a four-dimensional computed tomography (4D CT) includes receiving a 4D CT image set which contains a first three-dimensional computed tomographic image (3D CT) and a second 3D CT image. The method includes executing a deformable image registration (DIR) function on the received 4D CT image set, and determining a displacement vector field indicative of the lung motion induced by patient respiration. The method further includes segmenting the received 3D CT images into a first segmented image and a second segmented. The method includes determining the change in blood mass between the first 3D CT image and the second 3D CT image from the DIR solution, the segmented images, and measured CT densities.

An information processing apparatus includes an image obtaining unit configured to obtain a first inspection image having first supplemental information and a second inspection image having second supplemental information, a difference image obtaining unit configured to obtain a difference image generated using the first and second inspection images, a difference information obtaining unit configured to obtain difference information on a difference between the first supplemental information and the second supplemental information, and an association unit configured to associate the difference information with the difference image.

A system and method for improved image acquisition of multiple pulsed X-ray source-in-motion tomosynthesis imaging apparatus by generating the electrocardiogram (ECG) waveform data using an ECG device. Once a representative cardiac cycle is determined, system will acquire images only at rest period of heart beat. Real time ECG waveform is used as ECG synchronization for image improvement. The imaging apparatus avoids ECG peak pulse for better chest, lung and breast imaging under influence of cardiac periodical motion. As a result, smoother data acquisition, much higher data quality can be achieved. The multiple pulsed X-ray source-in-motion tomosynthesis machine is with distributed multiple X-ray sources that is spanned at wide scan angle. At rest period of one heartbeat, multiple X-ray exposures are acquired from X-ray sources at different angles. The machine itself has capability to acquire as many as 60 actual projection images within about two seconds.

A specific environmental stress on vegetation is calculated highly accurately and relatively easily. For generation of environmental stress information, vegetation information is obtained first using an imaging signal of vegetation. Furthermore, reference vegetation information associated with vegetation information in a state of being free of, for example, a specific environmental stress is obtained. Moreover, as information associated with an environmental stress on the vegetation, difference information between vegetation information acquired from an imaging signal of vegetation in a state of being likely to have the specific environmental stress and the reference vegetation information is obtained.

A medical scan report labeling system is operable to transmit a medical report that includes natural language text to a first client device for display. Identified medical condition term data is received from the first client device in response. An alias mapping pair in a medical label alias database is identified by determining that a medical condition term of the alias mapping pair compares favorably to the identified medical condition term data. A medical code that corresponds to the alias mapping pair and a medical scan that corresponds to the medical report are transmitted to a second client device of an expert user for display, and accuracy data is received from the second client device in response. The medical code is mapped to the first medical scan in the medical scan database when the accuracy data indicates that the medical code compares favorably to the medical scan.

The present application includes a method and a software architecture for measuring global longitudinal strain (GLS) and global longitudinal strain rate (GLSr) from 2D echocardiograms. In contrast to conventional GLS computation methods, this approach does not require boundary segmentation and regularization.

A medical report natural language model includes an artificial neural network implemented via the processor and is trained based a plurality of medical reports wherein each of the medical reports is mapped to at least one medical code of a plurality of medical codes and further based a plurality of medical condition terms from a plurality of alias mapping pairs, wherein each of the plurality of medical condition terms are unique, wherein each of the plurality of medical condition terms indicates a corresponding medical condition and wherein each of the plurality of alias mapping pairs includes a one of the plurality of medical condition terms and a corresponding single one of the plurality of medical codes that is a deterministic function of the one of the plurality of medical condition terms and wherein the plurality of alias mapping pairs includes two or more alias mapping pairs that map a corresponding two or more of the plurality of medical condition terms to a same one of the plurality of medical codes. A system operates by determining a first medical code of the plurality of medical codes utilizing the medical report natural language model on the first medical report by: recognizing, via the artificial neural network of the medical report natural language model, a first medical condition term of the plurality of medical condition terms in the first medical report; and determining the first medical code of the plurality of medical codes, based on the plurality of alias mapping pairs, wherein the determining the first medical code includes identifying a first alias mapping pair of the plurality of alias mapping pairs that pairs the first medical condition term deterministically to the first medical code; and mapping the first medical code of the plurality of medical codes and the first medical condition term of the plurality of medical condition terms to a first medical scan corresponding to the first medical report.

An apparatus, method and computer program is described comprising: receiving depth data for a first plurality of pixels of a video image of a scene; determining depth data over time for each of a second plurality of pixels of the video image, wherein the second plurality of pixels comprises at least some of the first plurality of pixels; and processing the determined depth data of successive instances of the second plurality of pixels to generate movement data, wherein each instance of the second plurality of pixels comprises depth data of the second plurality of pixels.

Disclosed herein a method of constructing a blood vessel map, the method including: receiving, by a blood vessel map construction apparatus, a TOF image of the object; extracting, by the blood vessel map construction apparatus, a blood vessel stem, a center line of a blood vessel, and features of the center line included in the TOF image, and detecting branch points of the blood vessel based on the extracted blood vessel stem, center line of the blood vessel, and features of the center line; searching, by the blood vessel map construction apparatus, a reference blood vessel image corresponding to the TOF image in consideration of location information or curvature information of the branch points; calculating a similarity between the TOF image and the reference blood vessel image; and registering the TOF image in the blood vessel map based on the similarity.

Systems and methods for determining corresponding locations of points of interest in a plurality of input medical images are provided. A plurality of input medical images comprising a first input medical image and one or more additional input medical images is received. The first input medical image identifies a location of a point of interest. A set of features is extracted from each of the plurality of input medical images. Features between each of the sets of features are related using a machine learning based relational network. A location of the point of interest in each of the one or more additional input medical images that corresponds to the location of the point of interest in the first input medical image is identified based on the related features. The location of the point of interest in each of the one or more additional input medical images is output.