Example anatomy map-based navigation systems and methods are disclosed and described. An example method includes displaying, via a graphical user interface, markers on an image, the markers corresponding to a plurality of marker types. The example method includes receiving a selection of a selected marker type from the plurality of marker types. The example method includes providing a synopsis overlaid on the image via the graphical user interface, the synopsis generated from historical data based on the selected marker type. The example method includes highlighting a subset of markers of the selected type on the image via the graphical user interface when the markers are included in the synopsis.

A method includes transitioning, via a micro-processor, an ultrasound imaging system (100) running in a first mode (128), in which a first location and a first orientation of an elongate needle (106) of an instrument (102) at a surface (111) of an object (110) is determined based on a first signal from a tracking device (112) at least on the instrument, to a second different mode, in which a second location and a second orientation of the needle within the object is determined based on an ultrasound image representing the object, in response to determining the needle penetrated the surface of the object, wherein a beam steering angle with which the ultrasound image is acquired is determined based on the first location and the first orientation of the needle, and displaying the ultrasound image.

A dynamic analysis system includes an imaging unit, an attenuation process unit and an analysis unit. The imaging unit images a dynamic state of a subject, thereby generating a plurality of frame images showing the dynamic state of the subject. The attenuation process unit performs an attenuation process to attenuate an image signal component of a product in the frame images. The analysis unit analyzes the dynamic state of the subject based on the frame images after the attenuation process.

A registration method whereby a sensor-based approach is used to establish initial registration and whereby upon the commencement of navigating an endoscope, image-based registration methods are used in order to more accurately maintain the registration between the endoscope location and previously-acquired images. A six-degree-of-freedom location sensor is placed on the probe in order to reduce the number of previously-acquired images that must be compared to a real-time image obtained from the endoscope.

An ophthalmic analysis apparatus for analyzing OCT motion contrast (MC) image data of a subject's eye acquired using an OCT apparatus for ophthalmology includes analysis process means for analyzing the OCT MC image data, in which the analysis process means generates OCT blood vessel change data including temporal change information in relation to a blood vessel region of the subject's eye based on first OCT MC image data and second OCT MC image data acquired at mutually different times.

A method for processing angiography image data by using an imaging catheter path that is directly detected from the angiography data as a co-registration path or using detected marker locations from the angiography data to generate a co-registration path. If the acquired angiography data includes synchronized cardiac phase signals and a predetermined quantity of angiography image frames not including contrast media, then a directly detected imaging catheter path is used as the co-registration path. Otherwise the co-registration path is determined based upon detected marker locations from the angiography image data.

The present application discloses a method of adjusting a parameter, the parameter being used to derive a physiological characteristic of an individual from an image of the user, the method comprising the steps of: obtaining the parameter for the individual; obtaining a corresponding parameter for a plurality of other individuals within a cohort of the individual; comparing the parameter for the individual with a statistically significant parameter for the plurality of other individuals; and adjusting the parameter for the individual in accordance with the difference between the parameter for the individual and the statistically significant parameter for the plurality of other individuals.

Machine logic (for example, software) for registering multiple medical images, each showing a common lesion, with each other. In performing this registration, registration points are chosen to be both: (i) outside of image portion that is potentially compromised by the lesion (in any of the multiple images); and (ii) as close to the lesion as possible. However, in at least one of the images the extent of the lesion is not knownso, in order to accommodate this uncertainty about the lesion boundaries, lesion predicting machine logic rules are used to predict the size, shape and/or location of the lesion. Machine learning is used to intermittently adjust and improve the lesion predicting machine logic rules.

A method for non-invasively classifying a tumorous modification of a tissue according to different stages of the tumorous modification comprises the steps of: a) receiving raw magnetic resonance imaging (MRI) data that has been recorded by applying at least one diffusion weighted imaging (DWI) sequence using three to nine different b-values to a tissue being suspicious to a tumorous modification without application of a contrast agent; b) extracting at least two quantification scheme parameters from the raw MRI data by using at least one quantification scheme, wherein each of the quantification scheme parameters is related to a microstructural property of the tissue; c) applying a weight to each quantification scheme parameter, wherein the weight is dependent on a kind of the tissue and on the quantification scheme, whereby a set of weighted quantification scheme parameters is obtained; d) determining a scoring value by combining the weighted quantification scheme parameters within the set, wherein each of the weighted quantification scheme parameters is used only once for determining the scoring value; and e) classifying the tumorous modification of the tissue into one of at least two classes according to the scoring value. The method and a corresponding classification device are capable of performing non-invasive tissue characterization without contrast agent administration in a highly accurate manner while supplementary information related to conventional imaging properties and clinical information can further increase the high diagnostic accuracy. They are used in their entirety for classifying the tumorous modification of the tissue.

An information processing apparatus (2000) detects an abnormal region (30) from a predetermined range (16) of a video frame (14). The information processing apparatus (2000) determines whether a predetermined condition is satisfied in a case where the abnormal region (30) is detected from the predetermined range (16) of a certain video frame (14) and the abnormal region (30) is not detected from the predetermined range (16) of a predetermined video frame (14) generated later than the video frame (14). In a case where the predetermined condition is not satisfied, the information processing apparatus (2000) performs a predetermined notification.