Intra-Operative Assessment of Cancer with X-Ray Phase Contrast Computed Tomography

X-ray Phase-Contrast Computed Tomography (PC-CT) increases contrast in weakly attenuating samples, such as soft tissues. In Edge-Illumination (EI) PC-CT, phase effects are accessed from amplitude modulation of the x-ray beam using alternating transmitting and attenuating masks placed prior to the sample and detector. A large field of view PC-CT scanner using this technique was applied to two areas of cancer assessment, namely excised breast and esophageal tissue. For the breast tissue, Wide Local Excisions (WLEs) were studied intra-operatively using PC-CT for the evaluation of tumor removal in breast conservation surgery. Images were acquired in 10 minutes without compromising on image quality, showing this can be used in a clinical setting. Longer, higher resolution PC-CT images were also taken, with analysis showing previously undetected thinning of tumor strands. This would allow a second use of the system for “virtual histopathology”, outside of surgery. For the esophagus samples, tissues were taken from esophagectomy surgery, where the lower part of the esophagus is removed, and the stomach relocated. For the assessment of ongoing therapy, accurate staging of tumors in the removed esophagus is essential, with the current gold standard provided by histopathology. PCCT images were acquired on several samples and compare well with histopathology, with both modalities showing similar features. Examples are shown where staging of tumor penetration is possible with PC-CT images alone, which is hoped will be an important step in performing the imaging and staging intra-operatively

Querying the Uncertain Position of Moving Objects

In this paper we propose a data model for representing moving objects with uncertain positions in database systems. It is called the Moving Objects Spatio-Temporal (MOST) data model. We also propose Future Temporal Logic (FTL) as the query language for the MOST model, and devise an algorithm for processing FTL queries in MOST. 1 Introduction Existing database management systems (DBMS's) are not well equipped to handle continuously changing data, such as the position of moving objects. The reason for this is that in databases, data is assumed to be constant unless it is explicitly modified. For example, if the salary field is 30K, then this salary is assumed to hold (i.e. 30K is returned in response to queries) until explicitly updated. Thus, in order to represent moving objects (e.g. cars) in a database, and answer queries about their position (e.g., How far is the car with license plate RWW860 from the nearest hospital?) the car's position has to be continuously updated. This is unsa..

Moving Objects Databases: Issues and Solutions

Consider a database that represents information about moving objects and their location. For example, for a database representing the location of taxi-cabs a typical query may be: retrieve the free cabs that are currently within 1 mile of 33 N. Michigan Ave., Chicago (to pick-up a customer). In the military, moving objects database applications arise in the context of the digital battlefield, and in the civilian industry they arise in transportation systems. Currently, moving objects database applications are being developed in an ad hoc fashion. Database Management System (DBMS) technology provides a potential foundation upon which to develop these applications, however, DBMS's are currently not used for this purpose. The reason is that there is a critical set of capabilities that are needed by moving objects database applications and are lacking in existing DBMS's. The objective of our Databases fOr MovINg Objects (DOMINO) project is to build an envelope containing these capabilities..

Location Management in Moving Objects Databases

In this paper we first introduce Moving Objects Databases and their related research problems. Then we concentrate on a particular problem, namely reducing the information cost associated with a trip taken by some moving object (e.g. a vehicle). The information cost of a trip consists of the overhead of position-update messages and the deviation of the database position from the actual position of the object. We introduce two position update policies, namely plain dead reckoning (pdr) and adaptive dead reckoning (adr). We show that adr has a lower information cost than pdr. 2 Introduction 2.1 Moving Objects Databases and Relevant Research Consider a database that represents information about moving objects and their position. For example, for a database representing the location of taxi-cabs a typical query may be: retrieve the free cabs that are currently within 1 mile of 33 N. Michigan Ave., Chicago (to pick-up a customer); or for a trucking company database a typical query may be:..

Updating and Querying Databases that Track Mobile Units

In this paper we consider databases representing information about moving objects (e.g. vehicles), particularly their location. We address the problems of updating and querying such databases. Specifically, the update problem is to determine when the location of a moving object in the database (namely its database location) should be updated. We answer this question by proposing an information cost model that captures uncertainty, deviation, and communication. Then we analyze dead-reckoning policies, namely policies that update the database location whenever the distance between the actual location and the database location exceeds a given threshold, x. Deadreckoning is the prevalent approach in military applications, and our cost model enables us to determine the threshold x. We propose several dead-reckoning policies and we compare their performance by simulation. Then we consider the problem of processing range queries in the database. An example of a range query is `retrieve the ob..