Browsing by Author "Verma, Romil"

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    COMPARISON OF 3D VOLUME REGISTRATION TECHNIQUES APPLIED TO NEUROSURGERY
    (Office of the Vice Chancellor for Research, 2012-04-13) Verma, Romil; Cottingham, Chris; Nguyen, Thanh; Kale, Ashutosh; Catania, Robin; Wright, Jacob; Christopher, Lauren; Tuceryan, Mihan; William, Albert
    Introduction: Image guided surgery requires that the pre-operative da-ta used for planning the surgery should be aligned with the patient during surgery. For this surgical application a fast, effective volume registration al-gorithm is needed. In addition, such an algorithm can also be used to devel-op surgical training presentations. This research tests existing methods of image and volume registration with synthetic 3D models and with 3D skull data. The aim of this research is to find the most promising algorithms in ac-curacy and execution time that best fit the neurosurgery application. Methods: Medical image volumes acquired from MRI or CT medical im-aging scans provided by the Indiana University School of Medicine were used as Test image cases. Additional synthetic data with ground truth was devel-oped by the Informatics students. Each test image was processed through image registration algorithms found in four common medical imaging tools: MATLAB, 3D Slicer, VolView, and VTK/ITK. The resulting registration is com-pared against the ground truth evaluated with mean squared error metrics. Algorithm execution time is measured on standard personal computer (PC) hardware. Results: Data from this extensive set of tests reveal that the current state of the art algorithms all have strengths and weaknesses. These will be categorized and presented both in a poster form and in a 3D video presenta-tion produced by Informatics students in an auto stereoscopic 3D video. Conclusions: Preliminary results show that execution of image registra-tion in real-time is a challenging task for real time neurosurgery applica-tions. Final results will be available at paper presentation. Future research will focus on optimizing registration and also implementing deformable regis-tration in real-time.
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    Securing Sensor Networks
    (Office of the Vice Chancellor for Research, 2012-04-13) ZareAfifi, Saharnaz; Verma, Romil; King, Brian
    Sensors can have significant impact on one's life. They can measure temperature, level of humidity, speed, motion, distance, light or the presence/absence of an object and many other phenomena and then these measurements can be processed together to provide the information that we use to make informative decisions. Today with the use of smart devices, such as iPhone, android phones, etc, we can interface with these sensors and use them in our daily lives. In the future, we will encounter even more intelligent and precise sensors, some that can significantly change our society. For example, consider sensors which can track eye movements and then process these movements to move the cursor within a windows session on a computer [1], envision how this could impact a paraplegic or even be applied within a computer aided surgical unit. Consider future sensors that can analyze the protein contents of a single cell and how they can be used in applications for medical diagnosis [2] or sensors that allow you to track and modify your energy usage [3]. Again, a potential conduit to these sensors may be our smart devices. In general, these sensors will provide us data, for which we can make decisions that improve our lives. In the future these sensors will be interconnected, data will be collected, and processed and automated decisions will be made and implemented by our smart devices. If humans collect the data to make information, i.e. make decisions, then the human can intercede when they view the data is inaccurate, but if devices make automated decisions then such information/decisions will be limited by the accuracy of the sensor data. We cannot rely on faulty information generated by inaccurate data. Faulty data can be generated by sensors that are acting improperly, perhaps because of a consumed power source (i.e. battery) or by entities, i.e. malicious parties, who infuse false data into the sensor network. The potential of a malicious party within the sensor network exists, and in order for us to rely on the sensor data we must be able to detect faulty data as well as malicious behavior (possibly by the sensor device). In this research project we will explore several potential attacks to the sensor network. In this work, we will briefly discuss two security problems. First, if a sensor is sending faulty data then the information generated can be faulty. This information is usually characterized as data aggregation (the data from multiple sensors is aggregated into information) and such an attack is characterized as the Data Aggregation attack. In this project, we will explore methods to detect the Data Aggregation attack and develop countermeasures to protect against the attack. Secondly, because malicious parties (or sensors) may exist, there is a potential in an automated system, of one device accusing another device of inappropriate behavior. For example, a malicious device may accuse other devices to avoid detection. This type of attack is characterized as the Reputation attack. In this work we will discuss the Reputation and Data Aggregation attacks, and develop power friendly countermeasures (fewer complexes with small amount of calculation) to these attacks.