We propose the use of conic and cubic surface equations (surfaces of second and third order) to directly approximate the dual-energy equations (the integral equations for the dual-energy log-signal functions, i.e., the negative logarithms of the relative detector signals, considered as functions of the basis-material component thicknesses of the object) and especially their inverses. These types of surface equations require a minimum number of calibration points, and their solutions are smooth, monotonic functions with the correct linear asymptotic behavior. The accuracy of this method is investigated and compared to that of conventional polynomial approximations, both for simulated and real calibration data, taken from two split-detector systems. These systems provide a more stringent test of our method than comparable dual-kVp systems, due to the greater nonlinearity of their log-signal and inverse functions. For these systems, we show that direct approximation of the inverse dual-energy equations using the simple eight-term rational form of the conic surface equation provides an extremely fast decomposition algorithm, which is accurate, robust in the presence of noise, and which can be calibrated with as few as 9 calibration points, or robustly calibrated, with a built-in accuracy check, using only 16 calibration points. Also, we show that extreme accuracy of approximation (to within less than 10(-6) in log-signal and 1 micron in material thickness) is theoretically attainable using the eighteen-term form of the cubic surface equation, which has a closed-form analytic solution. Finally, we consider the effects of noise on calibration accuracy, and derive simple formulas which relate the true and apparent root-mean-square (rms) accuracies. These formulas then allow the comparison of the true rms calibration accuracies of various surface approximations, considered as functions of the total calibration heat loading of the x-ray tube.

Abstract-Radical prostatectomy is performed on approximately 40% of men with organ-confined prostate cancer. Pathologic information obtained from the prostatectomy specimen provides important prognostic information and guides recommendations for adjuvant treatment. The current pathology protocol in most centers involves primarily qualitative assessment. In this paper, we describe and evaluate our system for automatic prostate cancer detection and grading on hematoxylin & eosin-stained tissue images. Our approach is intended to address the dual challenges of large data size and the need for high-level tissue information about the locations and grades of tumors. Our system uses two stages of AdaBoost-based classification. The first provides high-level tissue component labeling of a superpixel image partitioning. The second uses the tissue component labeling to provide a classification of cancer versus noncancer, and low-grade versus high-grade cancer. We evaluated our system using 991 sub-images extracted from digital pathology images of 50 whole-mount tissue sections from 15 prostatectomy patients. We measured accuracies of 90% and 85% for the cancer versus noncancer and high-grade versus low-grade classification tasks, respectively. This system represents a first step toward automated cancer quantification on prostate digital histopathology imaging, which could pave the way for more accurately informed postprostatectomy patient care.

The authors have devised a simple, fast and efficient method to optimize the number and position of catheters in interstitial HDR brachytherapy. The method was shown to be robust for both prostate and breast HDR brachytherapy. More importantly, the computation time of the algorithm is acceptable for clinical use. Ultimately, this catheter optimization algorithm could be coupled with a 3D ultrasound system to allow real-time guidance and planning in HDR brachytherapy.

Two approaches to estimate the optimal radiographic magnification for a TV camera-based portal imaging system and portal films have been used. The first approach optimizes signal transfer while the second optimizes signal-to-noise ratio (SNR) transfer. In order to perform these optimization calculations, the physical characteristics of the imaging system (modulation transfer function and noise power spectrum) as well as the sizes of the radiation sources of our medical linear accelerators have been measured. Using these data, the optimal magnification considering signal transfer alone (M signal) has been calculated to range between 2.0 and 2.3 for the TV camera-based imaging system and is about 1.0 for portal films. Conversely, the optimal magnification considering SNR transfer (MSNR) has been calculated to range between 1.5 and 1.7 for the TV camera-based imaging system and is about 1.0 for portal films. The results suggest that most portal imaging systems are operated close to their optimal radiographic magnification.

It is generally agreed that the conventional Trans-Rectal Ultrasound (TRUS) examination is an important, costeffective and useful technique for imaging the prostate. TRUS is used in the interpretation of the PSA assay, for monitoring response to nonsurgical and surgical therapy, andfor providing image guidance during some minimally invasive procedures. In This paper, multi-channel filtering is proposed as an excellent method for prostate texture investigation. By processing the TRUS images using multiple resolution techniques, the image is decomposed into appropriate texture features that can be used to classz/$ the textures accordingly. Using Human Visual system (HVS), Medical Doctors use three features for texture analysis, mainly repetition, directionality and complexiq. A bank ofGaborfi1ters that is well distributed to cover the entire frequency plane is designed to mimic the HVS and therefore it is an excellent tool that can be usedfor prostate texture segmentation.

Four tinplate specimens with different corrosion properties were studied using secondary ion mass spectrometry (SIMS) image analysis. The continuity of the structure of the interfacial iron‐tin alloy was able to be examined using a volume rendition computer program, which generates a three‐dimensional representation of the stack of ion images. The surface coverage of tinplate was found to vary widely on some specimens; those exhibiting poor corrosion characteristics were found to have little or no elemental tin covering the raised regions between the rolling grooves.

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It is proposed that digital scanned projection radiography of the chest be performed by using an energy-sensitive septaless xenon ionization detector (SXID) to obtain dual-energy images. The proposed detector is composed of a front region, sensitive to low-energy x rays, and a rear region, sensitive to high-energy x rays, separated by a suitable filter layer. We have developed a simple, precise theoretical formulation for dual-energy optimization, and applied it to the split SXID. We describe the variation of optimum detector performance with source kilovoltage and filtration (material and thickness), and hence heat loading, under conditions of constant exposure and constant dose. We estimate dose as the average absorbed dose to an equivalent water layer of suitable thickness, assuming slab geometry, so that the calculation is as simple as that for exposure.