Abstract: A tool circulates drilling fluid through and rotates a pipe string while making up or breaking out a stand of pipe. The tool includes a tubular member defining a central bore having an axis, wherein the tubular member comprises an upper tubular member and a lower tubular member, and wherein the upper tubular member and the lower tubular member are configured to alternately rotate independently and in unison. The tool also includes a central bore valve coupled to the upper member, and at least one radial valve coupled to the upper tubular member axially below the central bore valve.

Abstract: A downhole tool provided within a casing string for use in cement staging operations. The tool includes an inflatable packer that is integral to the body of the tool and ports in sides of the tool. The ports are selectively opened and closed for circulating cement from within the tool so that cement can flow between the casing string and a wellbore. The ports are actuated by sliding the casing string upward or downward within the wellbore. The packer can be pressure tested after being set to ensure its efficacy.

Abstract: A downhole tool incorporates a junk catcher with full body casing drift. It is made of an inner tubular member that conveys the hydraulic power or circulating fluid to rearward and outward facing jet nozzles for directly flushing downhole junks in front of the tool (if encountered) into a junk collecting barrel equipped with individual magnets to retain magnetically attractive metal junks. The barrel is made of high grade steel material with outer diameter matching the full drift of wellbore casing. The front, or the lower end of the outer body is addressed with tungsten carbide cutters to effectively handle metal junks in case of milling action is required. The back, or upper end of the barrel has return flow ports equipped with a filter screen to retain small, medium and large size junks while fluid is pumped through the tool.

Abstract: A method for detecting an object of interest in an input image includes the computer-implemented steps of: receiving an image, providing a multi-class pose classifier that identifies a plurality of pose features for estimating a pose of the object of interest, providing a plurality of cascades of serially-linked binary object feature classifiers, each cascade corresponding to different poses of the object of interest in the input image, selecting at least one of the cascades using the estimated pose, and employing the selected cascades to detect instances of the object of interest in the image.

Abstract: A method and system for regression-based object detection in medical images is disclosed. A regression function for predicting a location of an object in a medical image based on an image patch is trained using image-based boosting ridge regression (IBRR). The trained regression function is used to determine a difference vector based on an image patch of a medical image. The difference vector represents the difference between the location of the image patch and the location of a target object. The location of the target object in the medical image is predicted based on the difference vector determined by the regression function.

Abstract: A method for estimating a configuration of an internal structure within a medical image includes detecting a location of the internal structure. Component-based identification is performed within the detected location of the internal structure to identify a plurality of components. The configuration of the internal structure is estimated based on the relative position of the identified components.

Abstract: The present invention is directed to a method for populating a database with a set of images of an anatomical structure. The database is used to perform appearance matching in image pairs of the anatomical structure. A set of image pairs of anatomical structures is received, where each image pair is annotated with a plurality of location-sensitive regions that identify a particular aspect of the anatomical structure. Weak learners are iteratively selected and an image patch is identified. A boosting process is used to identify a strong classifier based on responses to the weak learners applied to the identified image patch for each image pair. The responses comprise a feature response and a location response associated with the image patch. Positive and negative image pairs are generated. The positive and negative image pairs are used to learn a similarity function. The learned similarity function and iteratively selected weak learners are stored in the database.

Abstract: A method for generating Pairwise Active Appearance Models (PAAMs) that characterize shape, appearance and motion of an object and using the PAAM to track the motion of an object is disclosed. A plurality of video streams is received. Each video stream includes a series of image frames that depict an object in motion. Each video stream includes an index of identified motion phases that are associated with a motion cycle of the object. For each video stream, a shape of the object is represented by a shape vector. An appearance of an object is represented by an appearance vector. The shape and appearance vectors associated at two consecutive motion phases are concatenated. Paired data for the concatenated shape and appearance vectors is computed. Paired data is computed for each two consecutive motion phases in the motion cycle. A shape subspace is constructed based on the computed paired data. An appearance subspace is constructed based on the computed paired data.

Abstract: A method for performing image based regression using boosting to infer an entity that is associated with an image of an object is disclosed. A regression function for a plurality of images is learned in which for each image the associated entity is known. The learned regression function is used to predict an entity associated with an image in which the entity is not known.

Abstract: Anatomical information is identified from a medical image and/or used for controlling a medical diagnostic imaging system, such as an ultrasound system. To identify anatomical information from a medical image, a processor applies a multi-class classifier. The anatomical information is used to set an imaging parameter of the medical imaging system. The setting or identification may be used in combination or separately.

Abstract: A system and method for identifying a shape of an anatomical structure in an input image is disclosed. An input image is received and warped using a set of warping templates resulting in a set of warped images. An integral image is calculated for each warped image. Selected features are extracted based on the integral image. A boosted feature score is calculated for the combined selected features for each warped image. The warped images are ranked based on the boosted feature scores. A predetermined number of warped images are selected that have the largest feature scores. Each selected warped image is associated with its corresponding warping template. The corresponding warping templates are associated with stored shape models. The shape of the input image is identified based on the weighted average of the shapes models.