Abstract: This invention relates to methods of producing aerogels and composites thereof. In particular, the invention relates to methods of producing silica aerogels and composites thereof. The invention also relates to doped aerogels and doped silica aerogels. The method involves the use of alkaline solutions, and particularly aqueous alkaline solutions, during the aerogel drying process. The method is more energy efficient and cheaper than prior art methods.

Abstract: The present disclosure relates to systems, methods, and computer-readable storage media for segmenting medical image. Embodiments of the present disclosure may locate and track a moving, three-dimensional (3D) target in a patient undergoing image-guided radiation therapy. For example, an adaptive filter model for a region of interest in the patient may be received, wherein the adaptive filter model is based on the target to be tracked. An image acquisition device may obtain a two-dimensional (2D) slice of a region of interest in the patient. A processor may then apply the adaptive filter model to the 2D slice, wherein the adaptive filter model includes an offset value. The processor may also determine a location of the target in the 2D slice based on the adaptive filter model. The processor may also estimate a potential location of the target based on the offset value. The processor may then repeat one or more of the above steps to track the moving target during image-guided radiation therapy of the patient.

Abstract: Network attack defense includes: obtaining a set of one or more statistical attributes for a protected site by gathering statistics for a set of one or more site attributes of the protected site, the site attributes indicating an operation mode of the protected site; determining, based on the set of one or more statistical attributes, that the protected site is to transition from a current operation mode to a target operation mode, wherein the current operation mode has a current defense strategy different from a target defense strategy of the target operation mode; and if the protected site is to transition from the current operation mode to the target operation mode, transitioning from the current operation mode to the target operation mode and applying the target defense strategy for the protected site instead of the current operation mode.

Abstract: The present disclosure relates to systems, methods, and computer-readable storage media for segmenting medical images. Embodiments of the present disclosure may relate to a method for segmenting medical images. The method may be implemented by a processor device executing a plurality of computer executable instructions. The method may comprise receiving an image from a memory, and identifying at least one landmark point within the image. The method may further comprise selecting an image point in the image, and determining at least one feature for the image point relative to the at least one landmark point. The method may also comprise associating the image point with an anatomical structure by using a classification model based on the at least one determined feature.

Abstract: The present disclosure relates to systems, methods, and computer-readable storage media for segmenting medical images. Embodiments of the present disclosure may relate to a method for segmenting medical images. The method may be implemented by a processor device executing a plurality of computer executable instructions. The method may comprise receiving an image from a memory, and identifying at least one landmark point within the image. The method may further comprise selecting an image point in the image, and determining at least one feature for the image point relative to the at least one landmark point. The method may also comprise associating the image point with an anatomical structure by using a classification model based on the at least one determined feature.

Abstract: The present disclosure relates to systems, methods, and computer-readable storage media for segmenting medical image. Embodiments of the present disclosure may locate a target in a three-dimensional (3D) volume. For example, an image acquisition device may provide a 3D medical image containing a region of interest of the target. A processor may then extract a plurality of two-dimensional (2D) slices from the 3D image. The processor may also determine a 2D patch for each 2D slice, wherein the 2D patch corresponds to an area of the 2D slice associated with the target. The processor may also convert the 2D patch to an adaptive filter model for determining a location of the region of interest.

Abstract: Embodiments disclose a method and system for segmenting medical images. In certain embodiments, the system comprises a database configured to store a plurality of medical images acquired by an image acquisition device. The plurality of images include at least one first medical image of an object, and a second medical image of the object, each first medical image associated with a first structure label map. The system further comprises a processor that is configured to register the at least one first medical image to the second medical image, determine a classifier model using the registered first medical image and the corresponding first structure label map, and determine a second structure label map associated with the second medical image using the classifier model.

Abstract: A method for performing automatic contouring in a medical image. The method may include receiving an image containing a region of interest and determining a first contour of the region of interest using a boundary detector. The method may include refining the first contour based on a shape dictionary to generate a second contour of the region of interest and updating at least one of the boundary detector or the shape dictionary based on the second contour.

Abstract: A method for performing automatic contouring in a medical image. The method may include receiving an image containing a region of interest and determining a first contour of the region of interest using a boundary detector. The method may include refining the first contour based on a shape dictionary to generate a second contour of the region of interest and updating at least one of the boundary detector or the shape dictionary based on the second contour.

Abstract: This invention relates to pharmaceutical composition and methods of using vitamin A and/or RAR? agonist for the treatment or prevention of diseases or conditions associated with high fat diet and/or vitamin deficiency.

Abstract: The present disclosure relates to systems, methods, and computer-readable storage media for segmenting medical image. Embodiments of the present disclosure may locate a target in a three-dimensional (3D) volume. For example, an image acquisition device may provide a 3D medical image containing a region of interest of the target. A processor may then extract a plurality of two-dimensional (2D) slices from the 3D image. The processor may also determine a 2D patch for each 2D slice, wherein the 2D patch corresponds to an area of the 2D slice associated with the target. The processor may also convert the 2D patch to an adaptive filter model for determining a location of the region of interest.

Abstract: A method for performing automatic contouring in a medical image. The method may include receiving an image containing a region of interest and determining a first contour of the region of interest using a boundary detector. The method may include refining the first contour based on a shape dictionary to generate a second contour of the region of interest and updating at least one of the boundary detector or the shape dictionary based on the second contour.

Abstract: The invention relates to a polyurethane (PU) reactive hot melt adhesive removable at elevated temperature as well as having a high bonding strength at room temperature.

Abstract: Systems and methods are provided for generating a pseudo-CT prediction model using multi-channel MR images. An exemplary system may include a processor configured to retrieve training data including multiple MR images and at least one CT image for each of a plurality of training subjects. For each training subject, the processor may determine at least one tissue parameter map based on the multiple MR images and obtain CT values based on the at least one CT image. The processor may also generate the pseudo-CT prediction model based on the tissue parameter maps and the CT values of the plurality of training subjects.

Abstract: Systems and methods are provided for generating a pseudo-CT prediction model that can be used to generate pseudo-CT images. An exemplary system may include a processor configured to retrieve training data including at least one MR image and at least one CT image for each of a plurality of training subjects. For each training subject, the processor may extract a plurality of features from each image point of the at least one MR image, create a feature vector for each image point based on the extracted features, and extract a CT value from each image point of the at least one CT image. The processor may also generate the pseudo-CT prediction model based on the feature vectors and the CT values of the plurality of training subjects.

Abstract: This invention relates to pharmaceutical composition and methods of using RXR agonist and/or RAR agonist for the treatment or prevention of head and neck cancer.

Abstract: This invention relates to pharmaceutical composition and methods of using vitamin A and/or RARB agonist for the treatment or prevention of diseases or conditions associated with high fat diet and/or vitamin deficiency. After smoking, high fat diet is said to be the second most lethal habit, causing 300,000 deaths each year in the U.S. alone. High fat diet leads to many health problems, including obesity, stroke, cancer, high blood pressure, diabetes, osteoarthritis, rheumatoid arthritis, multiple sclerosis, heart disease, and diseases in other organs such as liver and kidney.

Abstract: Various embodiments of the present disclosure provide improved systems and techniques for intelligently allocating cache requests to caches based upon the nature of the cache objects associated with the cache requests, and/or the condition of the caches in the distributed cache system, to facilitate cache system utilization and performance. In some embodiments, an allocation of cache requests may be performed in response to detection of a problem at one of a group of cache servers. For example, in some embodiments, a particular cache server may be entered into a safe mode of operations when the cache's ability to service cache requests is impaired. In other embodiments, an allocation of cache requests may be performed based on an cache object data type associated with the cache requests.

Abstract: Disclosed herein are techniques for enhancing the accuracy of atlas-based auto-segmentation (ABAS) using an automated structure classifier that was trained using a machine learning algorithm. Also disclosed is a technique for training the automated structure classifier using atlas data applied to the machine learning algorithm.

Abstract: The present disclosure relates to systems, methods, and computer-readable storage media for segmenting medical image. Embodiments of the present disclosure may locate a target in a three-dimensional (3D) volume. For example, an image acquisition device may provide a 3D medical image containing a region of interest of the target. A processor may then extract a plurality of two-dimensional (2D) slices from the 3D image. The processor may also determine a 2D patch for each 2D slice, wherein the 2D patch corresponds to an area of the 2D slice associated with the target. The processor may also convert the 2D patch to an adaptive filter model for determining a location of the region of interest.