A new method is presented for robustly estimating multiple view relations from point correspondences. The method comprises two parts. The first is a new robust estimator MLESAC which is a generalization of the RANSAC estimator. It adopts the same sampling strategy as RANSAC to generate putative

specifies the information format in which it is designed to operate. The authors show that Bayesian algorithms are computationally simpler in frequency formats than in the probability formats used in previous research. Frequency formats correspond to the sequential way information is acquired in natural

Abstract not found

A novel technique for the detection and enhancement of microcalcifications in digital tomosynthesis mammography (DTM) is presented. In this method, the DTM projection images are used directly, instead of using a 3D reconstruction. Calcification residual images are computed for each

Abstract. The problem of assessing the potential for dose reduction in X-ray mammography has been addressed in the paper [1] via numerical simulation, using the detection of microcalcifications as a benchmark to measure the loss of image quality in the dose-reduced images. In this paper we present

Abstract. The problem of assessing the potential for dose reduction in X-ray mammography has been addressed in the paper [1] via numerical simulation, using the detection of microcalcifications as a benchmark to measure the loss of image quality in the dose-reduced images. In this paper we present

simulated low-dose mammography

Abstract In a CAD system for the detection of masses, segmentation of mammograms yields regions of interest (ROIs), which are not only true masses but also suspicious normal tissues that result in false positives. We introduce a new method for false-positive reduction in this paper. The key idea

Abstrac t – Breast cancer i s the f irs t lead ing cause of dea th by cancer for women. To increase the survival rate i t i s necessary to detec t lesions as soon as poss ible. Most ear ly breas t cancer can be diagnosed by detec ting microcalc i f ica t ion clus ters in mammographic i mages. The c lus ters appear as groups of small, br ight par t ic les wi th arbi trary shapes and d is tr ibution. Because of human factors such as subject ive or varying decision cr i ter ia, d is tract ion by other image features, large number o f images to be inspected, o r s imple oversight, some diagnosis a re missed. In this paper, we propose a method to c lass i fy clus ters o f microca lci fica t ions charac ter iz ing the lesion by the extract ion of geometr ical (2D) and textural (3D) features. Then, through a stat is t ica l ana lys is o f these fea tures, we can choose the most discr iminat ing be tween benign and mal ignant les ions and so des ign the classi f ier. I.

The purpose of this article was to report the relationship between radiation dose and the ability of sentence digital mammography to detect microcalcifications. All images were acquired by computed radiography and an anthropo-morphic breast phantom. The tube voltage and anode/filter combination