Extracting well distributed control points (CPs) is a very challenging task for remote sensing image registration, particularly for large high-resolution images over heterogeneous landscape. Based on image analysis such as edge detection, corner detection, and information theory, a new CP detection approach is proposed to select high- quality, evenly distributed CPs. The Entropy-Block-Based variant of the Harris Corner Detector (EBB-HCD) is achieved by dividing the image into blocks and by allocating the number of CP's based upon the entropy of each block. While the block-based strategy improves the CP balance problem, a factor calculated from entropy avoids overdetection. We conducted a comparison study utilizing the well-known Harris Corner Detector (HCD) and an implementation of the Block-Based Harris Corner Detector (BB-HCD). Experimental results indicate that using EBB-HCD to find the CPs improves the overall alignment accuracy during registration compared with HCD or BB-HCD.
The objective of this study was to investigate the association between gaze patterns and the diagnostic performance of radiologists for the task of assessing the likelihood of malignancy of mammographic masses. Six radiologists (2 expert breast imagers and 4 Radiology residents of variable training) assessed the likelihood of malignancy of 40 biopsy-proven mammographic masses (20 malignant and 20 benign) on a computer monitor. Gaze data were collected using a commercial remote eye tracker. Upon reviewing each mass, the radiologists were asked to provide their assessment regarding the probability of malignancy of the depicted mass as well as a rating regarding the perceived difficulty of the diagnostic task. The collected gaze data were analyzed using established algorithms. Various quantitative metrics were extracted to characterize the recorded gaze patterns. The extracted metrics were correlated with the radiologists’ diagnostic decisions and perceived complexity scores. Results showed that the association between radiologists’ gaze metrics and their error making patterns varies, not only depending on the radiologists’ experience level but also among individuals. However, some gaze metrics appear to correlate with diagnostic error and perceived complexity more consistently. These results suggest that although gaze patterns are generally associated with diagnostic error and the perceived difficulty of the diagnostic task, there are substantial differences among individuals that are not explained simply by the training level of the individual performing the diagnostic task.
The biological concept of bilateral symmetry as a marker of developmental stability and good health is well established. Although most individuals deviate slightly from perfect symmetry, humans are essentially considered bilaterally symmetrical. Consequently, increased fluctuating asymmetry of paired structures could be an indicator of disease. There are several published studies linking bilateral breast size asymmetry with increased breast cancer risk. These studies were based on radiologists’ manual measurements of breast size from mammographic images. We aim to develop a computerized technique to assess fluctuating breast volume asymmetry in screening mammograms and investigate whether it correlates with the presence of breast cancer. Using a large database of screening mammograms with known ground truth we applied automated breast region segmentation and automated breast size measurements in CC and MLO views using three well established methods. All three methods confirmed that indeed patients with breast cancer have statistically significantly higher fluctuating asymmetry of their breast volumes. However, statistically significant difference between patients with cancer and benign lesions was observed only for the MLO views. The study suggests that automated assessment of global bilateral asymmetry could serve as a breast cancer risk biomarker for women undergoing mammographic screening. Such biomarker could be used to alert radiologists or computer-assisted detection (CAD) systems to exercise increased vigilance if higher than normal cancer risk is suspected.
Ambient light in a scene can introduce errors into range data from most commercial three-dimensional range scanners, particularly scanners that are based on projected patterns and structured lighting. We study the effects of ambient light on a specific commercial scanner. We further present a method for characterizing the range accuracy as a function of ambient light distortions. After a brief review of related research, we first describe the capabilities of the scanner we used and define the experimental setup for our study. Then we present the results of the range characterization relative to ambient light. In these results, we note a systematic error source that appears to be an artifact due to a structured light pattern. We conclude with a discussion of this error and the physical meaning of the results overall.
The purpose of this research is to investigate imaging-based methods to reconstruct 3D CAD models of real-world objects. The methodology uses structured lighting technologies such as coded-pattern projection and laser-based triangulation to sample 3D points on the surfaces of objects and then to reconstruct these surfaces from the
dense point samples. This reverse engineering (RE) research presents reconstruction results for a military tire that is important to tire-soil simulations. The limitations of this approach are the current level of accuracy that imaging-based systems offer relative to more traditional CMM modeling systems. The benefit however is the potential for denser point samples and increased scanning speeds of objects, and with time, the imaging technologies should continue to improve to compete with CMM accuracy. This approach to RE should lead to high fidelity models of manufactured and prototyped components for comparison to the original CAD models and for simulation analysis. We focus this paper on the data collection and view registration problems within the RE pipeline.
The characterization of commercial 3D scanners allows acquiring precise and useful data. The accuracy of range and, more recently, color for 3D scanners is usually studied separately, but when the 3D scanner is based on structured light with a color coding pattern, color influence on range accuracy should be investigated. The commercial product that we have tested has the particularity that it can acquire data under ambient light instead of a controlled environment as it is with most available scanners. Therefore, based on related work in the literature and on experiments we have done on a variety of standard illuminants, we have designed an interesting setup to control illuminant interference. Basically, the setup consists of acquiring the well-known Macbeth ColorChecker under a controlled environment and also ambient daylight. The results have shown variations with respect to the color. We have performed several statistical studies to show how the range results evolve with respect to the RGB and the HSV channels. In addition, a systematic noise error has also been identified. This noise depends on the object color. A subset of colors shows strong noise errors while other colors have minimal or even no systematic error under the same illuminant.