Abstract: Ultrasound imaging systems and methods are disclosed. In one embodiment, an ultrasongraphy method includes creating a database that is representative of a tissue, a fluid, or a cavity of a body, and transmitting ultrasound pulses into a region-of-interest in a patient. Echoes are received from the region of interest, and based upon the received echoes, compiling an ultrasonic pattern of the region-of-interest is compiled. The pattern is processed by comparing the region-of-interest patterns to the pattern information stored in the database. A composition within the region-of-interest of the patient is then determined.

Abstract: A segmentation algorithm is optimized to robustly locate and measure the volume of fluid filled or non-fluid filled structures or organs from imaging systems derived from ultrasound, computer assisted tomography, magnetic resonance, and position emission tomography. A clinical specimen is measured with a plurality of 2D scan planes processed by the segmentation algorithm to estimate the 2D based area the 3D based volumes of fluid-filled and non-fluid filled organs or structures.

Abstract: A system and method to acquire 3D ultrasound-based images during the end-systole and end end-diastole time points of a cardiac cycle to allow determination of the change and percentage change in left ventricle volume at the time points.

Abstract: A system which includes at least one ultrasound data collection device which is programmable to carry out a specific ultrasound procedure on a selected part of a human body of a patient. The resulting ultrasound data is transmitted via a local server at the site of the data collection device to the internet and from there to a web database server which processes the raw ultrasound data to produce medical result information, including ultrasound images, which is then sent to a skilled technician, who accepts the results, rejects or edits them. Accepted medical results are transmitted back to the medical practitioner, while edited medical results are reprocessed, the results of which are transmitted to the medical practitioner.

Abstract: A hand-held 3D ultrasound instrument is disclosed which is used to non-invasively and automatically measure amniotic fluid volume in the uterus requiring a minimum of operator intervention. Using a 2D image-processing algorithm, the instrument gives automatic feedback to the user about where to acquire the 3D image set. The user acquires one or more 3D data sets covering all of the amniotic fluid in the uterus and this data is then processed using an optimized 3D algorithm to output the total amniotic fluid volume corrected for any fetal head brain volume contributions.

Abstract: An ultrasound transceiver scans an organ and processes the echogenic signals to produce three-dimensional, two-dimensional, and one-dimensional information of the organ. The 3-D, 2-D, and 1-D information is utilized to determine the thickness, surface area, volume, and mass of the organ wall.

Abstract: A hand-held 3D ultrasound instrument is disclosed which is used to non-invasively and automatically measure amniotic fluid volume in the uterus requiring a minimum of operator intervention. Using a 2D image-processing algorithm, the instrument gives automatic feedback to the user about where to acquire the 3D image set. The user acquires one or more 3D data sets covering all of the amniotic fluid in the uterus and this data is then processed using an optimized 3D algorithm to output the total amniotic fluid volume corrected for any fetal head brain volume contributions.

Abstract: An ultrasound transceiver scans a bladder in a three dimensional array to measure the thickness and surface area of the bladder to determine bladder mass. The bladder wall thickness and masses may be determined for anterior, posterior, and lateral locations of the bladder.

Abstract: A segmentation algorithm is optimized to robustly locate and measure the volume of fluid filled or non-fluid filled structures or organs from imaging systems derived from ultrasound, computer assisted tomography, magnetic resonance, and position emission tomography. A clinical specimen is measured with a plurality of 2D scan planes processed by the segmentation algorithm to estimate the 2D based area the 3D based volumes of fluid-filled and non-fluid filled organs or structures.

Abstract: A hand-held 3D ultrasound instrument is disclosed which is used to non-invasively and automatically measure amniotic fluid volume in the uterus requiring a minimum of operator intervention. Using a 2D image-processing algorithm, the instrument gives automatic feedback to the user about where to acquire the 3D image set. The user acquires one or more 3D data sets covering all of the amniotic fluid in the uterus and this data is then processed using an optimized 3D algorithm to output the total amniotic fluid volume corrected for any fetal head brain volume contributions.

Abstract: A system for image registration and quantitative feature extraction for multiple image sets. The system includes an imaging workstation having a data processor and memory in communication with a database server in communication. The a data processor capable of inputting and outputting data and instructions to peripheral devices and operating pursuant to a software product and accepts instructions from a graphical user interface capable of interfacing with and navigating the imaging software product. The imaging software product is capable of instructing the data processor, to register images, segment images and to extract features from images and provide instructions to store and retrieve one or more registered images, segmented images, quantitative image features and quantitative image data and from the database server.

Abstract: A hierarchy of deformation operations is implemented to deform a template and match the deformed template to an object in a video frame. At each level, the constraints on the template deformations are relaxed, while the spatial range of the object boundary search is narrowed. At a highest level, an initial template is translated, rotated and scaled to coarsely locate the object within a given image frame. At a middle level, an affine transformation is implemented, globally or locally, to deform the template. For a local affine transformation process, a sup-portion, such as an articulation or appendage portion of the template is deformed. The middle level refines the template to get the template boundary close to the actual object boundary within a given frame. At the lowest level, a local segmentation algorithm is applied to deform the now close boundary to finely match the object boundary.

Abstract: An ultrasound system automatically measures fetal head size from ultrasound images. An ultrasound image of the fetal head is detected. A radial maxima point is identified on each of a plurality of radii extending from a substantially common vertex point within the fetal head image. Each radial maxima point corresponds to an ultrasound sample along its corresponding radius, and has a maximum ultrasound echo strength. Outlier points are removed and the curve filtered to derive an initial fetal head boundary. An inner fetal head boundary and outer fetal head boundary are derived from the initial fetal head boundary and a predetermined fetal skull thickness, and fetal head size is computed from the inner fetal head boundary and the outer fetal head boundary. Processing is allocated among multiprocessors and performed in pipeline fashion to enable real-time interactive imaging and measuring.

Abstract: An ultrasound system automatically measures fetal head size from ultrasound images. An ultrasound image of the fetal head is detected. A radial maxima point is identified on each of a plurality of radii extending from a substantially common vertex point within the fetal head image. Each radial maxima point corresponds to an ultrasound sample along its corresponding radius, and has a maximum ultrasound echo strength. A first curve is defined from the radial maxima points. The remaining unfiltered radial maxima points are fit to a second curve, and the second curve is the detected curved boundary. The detected curve boundary is modified to define an initial fetal head boundary. An inner fetal head boundary and outer fetal head boundary are derived from the initial fetal head boundary and a predetermined fetal skull thickness, and fetal head size is computed from the inner fetal head boundary and the outer fetal head boundary.