A system includes one or more sensors to detect activities of a mobile object; and a processor coupled to the sensor and the wireless transceiver to classify sequences of motions into groups of similar postures each represented by a model and to apply the models to identify an activity of the object.

Ultrasound-based acoustic streaming for deciding whether material is fluid is dependent upon any one or more of a variety of criteria. Examples are displacement, speed (230), temporal or spatial flow variance, progressive decorrelation, slope or straightness of accumulated signal to background comparisons over time, and relative displacement to adjacent soft tissue. Echogenicity-based area identification is combinable with the above movement characteristic detection in the deciding. Fluid pool identification is performable from the area-limited acoustic streaming testing and ultrasound attenuation readings. Candidates from among the areas (210) are screenable based on specific shapes or bodily organs detected. Natural flow can be excluded from streaming detection by identification of blood vessels (206). Processing for each FAST ultrasound view (202), or for the entire procedure, is performable automatically, without need for user intervention or with user intervention to identify suspected areas.

Mechanisms for image processing are provided. A computing device comprises a memory, an input device, a display, and a processor. The processor is configured to: acquire a three-dimensional image of an anatomical structure and store it in the memory. The processor renders on the display (i) an initial volume of the three-dimensional image corresponding to an initial portion of the anatomical structure, and (ii) a moveable control element. The initial volume has an outer surface defined by a position of the control element. The processor receives input data updating the position of the control element relative to the initial volume; and renders on the display, in place of the initial volume, a further volume of the three-dimensional image, corresponding to a further portion of the anatomical structure and having a further outer surface defined by the updated position of the control element.

A method of adaptive image acquisition includes obtaining a guide image of patient tissue; receiving an intraoperative image of a portion of the patient tissue from an imaging instrument; and storing the intraoperative image. The method includes comparing the intraoperative image with the guide image to identify at least one region of the guide image matching the intraoperative image; and determining whether the at least one region identified meets at least one accuracy criterion. When the at least one region meets the at least one accuracy criterion, the guide image is rendered with an indication of the at least one region on a display. When the at least one region does not meet the at least one accuracy criterion, the method includes receiving and storing a further intraoperative image; combining the further intraoperative image with the intraoperative image; and repeating the comparing and determining.

A processing system and a confocal processing method for confocally emitting and receiving ultrasound. Firstly, a first driving electrical signal is generated. Then, at least one first ultrasound signal having a main frequency is emitted to a reflection position according to the first driving electrical signal. With an object at the reflection position, the first ultrasound signal is reflected to form at least one second ultrasound signal. Then, a first analyzed signal whose frequency lower than the main frequency is retrieved from the second ultrasound signal, and other signals are eliminated from the second ultrasound signal, and the first analyzed signal is converted into at least one first analogous signal. Finally, first energy of a first fixed bandwidth of the first analyzed signal is retrieved by the first analogous signal. The method stops generating the first driving electrical signal when the first energy is larger than a predetermined value.

Various aspects of a system and a method to provide assistance in a surgery in presence of tissue deformation are disclosed herein. In accordance with an embodiment, the system includes an electronic device that receives one or more tissue material properties of a plurality of surface structures of an anatomical portion. One or more boundary conditions associated with the anatomical portion may also be received. Surface displacement of the anatomical portion may be determined by matching a first surface of the anatomical portion before deformation with a corresponding second surface of the anatomical portion after the deformation. The volume displacement field of the anatomical portion may be computed based on the determined surface displacement, the received one or more tissue material properties, and the received one or more boundary conditions.

The invention relates to a medical data processing method for determining a vulnerability field of a brain of a patient, the steps of the method being constituted to be executed by a computer and comprising: a) acquiring a nerve-indicating dataset comprising information about the brain of the patient suitable for identifying neural fibers in the brain of the patient; b) determining nodes within the brain preferably being neuron-rich grey matter parts of the brain; c) determining the axonal linkage of the nodes based on the nerve-indicating dataset to obtain edges connecting the nodes, the nodes and edges constituting a connectivity graph; d) determining a weight for each of the edges depending on centrality graph theoretical statistical measure of the respective edge in the connectivity graph; e) determining, for each of the edges, which voxels in a dataset of the brain of the patient belong to the edges or are passed by the edges and assigning or adding the determined weight of the respective edges to all of the voxels belonging to the respective edge to obtain a weighted voxel-based dataset of the brain of the patient defining the vulnerability field of the brain.

A display pixel array is illuminated by infrared light in a frequency band. An infrared holographic imaging signal is generated by driving a holographic pattern onto the display pixel array. An image of an exit signal of the holographic infrared imaging signal is captured with an image pixel array. The image pixel array is configured to capture the infrared light and reject light outside the frequency band.

A novel method to noninvasively measure intracranial pressure (ICP) and more generally brain elasticity is disclosed. ICP is determined using an algorithm coupled on a simulated artificial neural network (SANN) that calculates ICP based on a determination of a set of interacted ultrasound signals (IUSs) generated from multiple ultrasound pulses. The methods and systems of the present invention are capable of rapidly determining ICP without manual review of EPG waves by a technician.

According to various embodiments, there is provided a probe structure. The probe structure includes a probe configured to emit acoustic energy. The probe structure further includes a load cell underneath and aligned with the probe. The probe structure further includes a probe hub including a cavity for receiving the probe and the load cell.