Disclosed are methods and apparatus for viewing a contrast-enhanced ultrasound image and a dynamic data. The method comprises: receiving a first operation, for setting a first viewing range by a first browsing step length that is multiple frames; in response to the first operation, positioning the image data to a viewing neighborhood containing the first viewing range; receiving a second operation, on the view neighborhood by a second browsing step length that is a single frame; in response to the second operation, determining a current image frame corresponding to when the second operation is performed in the viewing neighborhood, and further positioning the image data to an adjacent frame of the current image frame to the user to view frame by frame. As such, doctors are helped to accurately locate desired image frames to significantly improve browsing efficiency with convenient operation and high user-friendliness to save time and reduce workload.

Embodiments relate to a sensor system for a brain computer interface (BCI) that enable detection and decoding of brain activity by optical tomography. The sensor system includes an array of pixels arranged as grouped pixel units to provide increased dynamic range. One or more of the grouped pixel units can operate in a saturated mode while providing information useful for decoding brain activity. Furthermore, the grouped pixel units are arranged to enable fast readout by a pixel scanner, thereby increasing detection and decoding ability by systems implementing the sensor design. The grouped pixel units of the sensor system are aligned with optical fibers of an interface to a body region of a user, where the optical fibers can be retained in position relative to the grouped pixel units by an optically transparent substrate that provides mechanical support while minimizing factors associated with divergence of light transmitted through optical fibers.

A method and apparatus is provided that uses a deep learning (DL) network to reduce noise and artifacts in reconstructed medical images, such as images generated using computed tomography, positron emission tomography, and magnetic resonance imaging. The DL network can operate either on pre-reconstruction data or on a reconstructed image. The DL network can be an artificial neural network or a convolutional neural network (e.g., using a three-channel volumetric kernel architecture). Different neural networks can be trained depending on the noise level, scanning protocol, or the anatomic, diagnostic or clinical objective of the reconstructed image (e.g., by partitioning the training data into noise-level range and training respective DL networks for each range). Further, the DL networks can be trained to mitigate artifacts, such as the cone-beam artifact.

An optimized press-fit between a resected bone and an articular implant may, for instance, reduce undesirable qualities, including excess micromotion, stress transmission, and/or strain. By taking into account heterogeneous bone properties, the parameters of a bone resection can be determined as to optimize the press-fit between a resected bone and an articular implant. An optimized press-fit is obtained by determining ideal engagement characteristics corresponding to the fit between the fixation features of an articular implant and a bone. Then, taking into account a bone's heterogeneous properties, the parameters of a bone resection that would substantially achieve the determined ideal engagement characteristics are determined.

An evaluation method and system for the corrosion degree of an absorbable stent. The method includes the following steps: obtaining the total number S.sub.0 of stent bars of the absorbable stent at the time zero of implantation (S10); separately obtaining n frames of optical coherence tomography (OCT) images of the absorbable stent at the time x of implantation, wherein x is greater than 0, and n is a natural number greater than 1 (S20); determining, according to the n frames of OCT images, the total number Ni of the stent bars corresponding to each frame of OCT image, wherein i is a natural number greater than or equal to 1 and less than or equal to n; and calculating the total number S.sub.x of the stent bars corresponding to the n frames of OCT images at the time x of implantation (I) (S30); determining a corrosion degree Cij of a jth stent bar in an ith frame of OCT image at the time x of implantation, wherein j is a natural number greater than or equal to 1 and less than or equal to Ni (S40); and calculating an overall corrosion degree Cx of the absorbable stent at the time x of implantation according to the following formula: (II) (S50). The evaluation method can be applied to clinical treatment.

A method of determining axial alignment of a lower limb includes determining a three-dimensional volume based on a scan of a lower limb of a patient, identifying a level of hip version by referring to a first axis of symmetry of a femoral neck and a second axis of symmetry of a distal portion of a femur, wherein hip version is defined by an angle between the first axis of symmetry and the second the second axis of symmetry, identifying a level of tibial torsion by referring to a third axis of symmetry of a proximal portion of a tibia and a fourth axis of symmetry of a distal portion of the tibia, wherein tibial torsion is defined by an angle between the third axis of symmetry and the fourth axis of symmetry, and providing the level of hip version and the level of tibial torsion to a user.

Methods and systems for providing treatment planning information for a neurology procedure, including neurosurgical procedures. A database containing historical data about historical procedures is accessed. Historical data relevant to a neurology procedure is determined, based on a determination of similarity to a set of data characterizing the neurology procedure. Historical instances of procedure parameters relevant to the neurology procedure are determined and displayed.

Disclosed herein are monoclonal antibodies targeting specific tau epitopes, particularly, microtubule binding domain region 2 or region 4. Also disclosed herein are antibodies or antigen binding fragments thereof that specifically recognize a tau epitope consisting of the amino acid sequence of SEQ ID NO: 9 or 11. Also disclosed herein are methods of detecting tau protein in a subject, comprising performing an assay using the antibodies or antigen binding fragments thereof on the subject or on a biological sample obtained from the subject. Assay kits containing the disclosed antibodies are also provided. Further, methods of treating or preventing a tauopathy in a subject by administering to the subject tau antibodies or antigen-binding fragments thereof are provided.

An optical measurement system includes a wearable device including a support assembly configured to be worn on a body of a user and a wearable assembly supported by the support assembly. The wearable assembly includes a plurality of light sources configured to emit a plurality of light pulses toward a target within the body of the user and a plurality of detectors each configured to receive a set of photons included in a light pulse included in the plurality of light pulses after the set of photons is scattered by the target. A position of the wearable assembly on the support assembly is adjustable.

A ferrule is configured to optically coupled to electronics for detect signals from a head of a user. The ferrule has optical properties to guide light between the electronics and a head of a user. The ferrule comprises a base portion having a cavity to enclose an optical element, a middle portion configured to guide light to or from the optical element, and a tip portion to interface with the head of the user.