Abstract: A method is provided for detecting lesions in ultrasound images. The method includes acquiring ultrasound information, determining discriminative descriptors that describe the texture of a candidate lesion region, and classifying each of the discriminative descriptors as one of a top boundary pixel, a lesion interior pixel, a lower boundary pixel, or a normal tissue pixel. The method also includes determining a pattern of transitions between the classified discriminative descriptors, and classifying the candidate lesion region as a lesion or normal tissue based on the pattern of transitions between the classified discriminative descriptors.

Abstract: Sharing of content by users via the network is facilitated. Sharing suggestions are made to a user, the sharing suggestions including making a suggestion of one or more users with whom the user might wish to share content. A user's influence on other users and the user can be prompted to share content with other users based on the identified influence.

Abstract: Examples of secure application development and execution are disclosed herein. An example method may include parsing code of an application configured for execution on a user device to identify one or more sensitive portions of the code. Example methods may further include identifying a trusted execution environment, different from the user device, suitable to execute the one or more sensitive portions of the code. Example methods may further include configuring the code to provide the one or more sensitive portions of the code from the user device to the trusted execution environment during execution of the application on the user device.

Abstract: Examples of methods, systems, products, devices, and/or apparatus generally related to mobile security are described. An example method may include capturing a context pattern of a user device. The context pattern may be based, at least in part, on data from one or more sensors of the user device. The data may be acquired at multiple different times. The example method may further include generating at least one public-private key pair based, at least in part, on the context pattern.

Abstract: Examples of methods, systems, products, devices, and/or apparatus generally related to mobile security are described. An example method may include capturing a context pattern of a user device. The context pattern may be based, at least in part, on data from one or more sensors of the user device. The data may be acquired at multiple different times. The example method may further include generating at least one public-private key pair based, at least in part, on the context pattern.

Abstract: Examples of methods, systems, products, devices, and/or apparatus generally related to mobile security are described. An example method may include capturing a context pattern of a user device. The context pattern may be based, at least in part, on data from one or more sensors of the user device. The data may be acquired at multiple different times. The example method may further include generating at least one public-private key pair based, at least in part, on the context pattern.

Abstract: A method is provided for detecting lesions in ultrasound images. The method includes acquiring an ultrasound image, generating a Fisher-tippett (FT) distribution-based edge feature map from the acquired ultrasound image, generating gradient concentration (GC) scores for pixels of the acquired ultrasound image using the FT distribution-based edge feature map, and identifying a candidate lesion region within the acquired ultrasound image based on the GC scores.

Abstract: Technologies are generally described for generating policies for multiple devices associated with a user. In some examples, one or more policies associated with a user may be accessed. The policies may pertain to one or more computing devices associated with the user. The capabilities of an additional computing device to be associated with the user may be determined. Based on the determined capabilities, which of the one or more policies are applicable to the additional computing device may be identified. Based on the identified policies, a default set of policies for the additional computing device may be automatically generated.

Abstract: Examples of secure application development and execution are disclosed herein. An example method may include parsing code of an application configured for execution on a user device to identify one or more sensitive portions of the code. Example methods may further include identifying a trusted execution environment, different from the user device, suitable to execute the one or more sensitive portions of the code. Example methods may further include configuring the code to provide the one or more sensitive portions of the code from the user device to the trusted execution environment during execution of the application on the user device.

Abstract: A method for detecting a lesion in an anatomical region of interest is presented. The method includes identifying one or more candidate mass regions in each of a plurality of 3D ultrasound images acquired at different view angles from the anatomical region of interest. Single-view features corresponding to each candidate mass region are identified. For a candidate mass region, a similarity metric between the single-view features corresponding to the candidate mass region and the single-view features corresponding to the other candidate mass regions is determined. The candidate mass region is classified based at least on the similarity metric. A system for imaging and a non-transitory computer readable media for detection of the lesion are also presented.

Abstract: A method is provided for detecting lesions in ultrasound images. The method includes acquiring an ultrasound image, generating a Fisher-tippett (FT) distribution-based edge feature map from the acquired ultrasound image, generating gradient concentration (GC) scores for pixels of the acquired ultrasound image using the FT distribution-based edge feature map, and identifying a candidate lesion region within the acquired ultrasound image based on the GC scores.

Abstract: A method is provided for detecting lesions in ultrasound images. The method includes acquiring ultrasound information, determining discriminative descriptors that describe the texture of a candidate lesion region, and classifying each of the discriminative descriptors as one of a top boundary pixel, a lesion interior pixel, a lower boundary pixel, or a normal tissue pixel. The method also includes determining a pattern of transitions between the classified discriminative descriptors, and classifying the candidate lesion region as a lesion or normal tissue based on the pattern of transitions between the classified discriminative descriptors.

Abstract: Sharing of content by users via the network is facilitated. Sharing suggestions are made to a user, the sharing suggestions including making a suggestion of one or more users with whom the user might wish to share content. A user's influence on other users and the user can be prompted to share content with other users based on the identified influence.

Abstract: A video imager may be used to measure the natural and/or artificial light levels in a space. The lighting estimates may be passed to a controller via a communication network. The lighting estimates may be in the form of actual radiance values, brightness, or other forms. The controller may determine if and which areas of the space require more light or if and which areas of the space have more light than required. Based on the lighting estimates, the controller may issue commands to turn on/off or dim/brighten the light from various ones or combinations of light sources in or around the space via actuators. The controller may also directly interface with the light sources.

Abstract: A video imager may be used to measure the natural and/or artificial light levels in a space. The lighting estimates may be passed to a controller via a communication network. The lighting estimates may be in the form of actual radiance values, brightness, or other forms. The controller may determine if and which areas of the space require more light or if and which areas of the space have more light than required. Based on the lighting estimates, the controller may issue commands to turn on/off or dim/brighten the light from various ones or combinations of light sources in or around the space via actuators. The controller may also directly interface with the light sources.