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Noninvasive, radiological image-based detection and stratification of Gleason patterns can impact clinical outcomes, treatment selection, and the determination of disease status at diagnosis without subjecting patients to surgical biopsies. We present machine learning-based automatic classification of prostate cancer aggressiveness by combining apparent(More)
One of the most important tasks for mobile robots is to sense their environment. Further tasks might include the recognition of objects in the surrounding environment. Three dimensional range finders have become the sensors of choice for mapping the environment of a robot. Recognizing objects in point clouds provided by such sensors is a difficult task. The(More)
Cameras are becoming a common tool for automated vision purposes due to their low cost. In an era of growing security concerns, camera surveillance systems have become not only important but also necessary. Algorithms for several tasks such as detecting abandoned objects and tracking people have already been successfully developed. While tracking people is(More)
Cameras are becoming a common tool for automated vision purposes due to their low cost. Many surveillance and inspection systems include cameras as their sensor of choice. How useful these camera systems are is very dependent upon the positioning of the cameras. This is especially true if the cameras are to be used in automated systems as a beneficial(More)
To investigate Haralick texture analysis of prostate MRI for cancer detection and differentiating Gleason scores (GS). One hundred and forty-seven patients underwent T2- weighted (T2WI) and diffusion-weighted prostate MRI. Cancers ≥0.5 ml and non-cancerous peripheral (PZ) and transition (TZ) zone tissue were identified on T2WI and apparent diffusion(More)
With the proliferation of security cameras, the approach taken to monitoring and placement of these cameras is critical. This paper presents original work in the area of multiple camera human activity monitoring. First, a system is presented that tracks pedestrians across a scene of interest and recognizes a set of human activities. Next, a framework is(More)
In this paper, we introduce a new covariance based feature descriptor to be used on “colored” point clouds gathered by a mobile robot equipped with an RGB-D camera. Although many recent descriptors provide adequate results, there is not yet a clear consensus on how to best tackle “colored” point clouds. We present the notion of a(More)
A robot that can drive autonomously, actively seeking more information about the environment as it attempts to infer it, has significant value in many application areas. Range scanners and depth sensors are one of the most popular sensors used in mobile robotics to accomplish several higher level tasks such as local planning, obstacle avoidance, and mapping(More)