Yasemin Yardimci

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In this paper, computer-aided diagnosis of microcalcification clusters in mammogram images is considered. Microcalcification clusters which are an early sign of breast cancer appear as isolated bright spots in mammogram images. Therefore they correspond to local maxima of the mammogram image. In our method we first detect the local maxima of the image, and(More)
A new method for detecting microcalcifications in mammograms is described. In this method, the mammogram image is first processed by a subband decomposition filterbank. The bandpass subimage is divided into overlapping square regions in which skewness and kurtosis as measures of the asymmetry and impulsiveness of the distribution are estimated. The(More)
An automated hazelnut classification system is developed using sub-band information of impact acoustic signal taken from hazelnut kernels. It is observed that hazelnuts emit different acoustic signals when they impact on a metal plate. Impact acoustic signal of nuts are decomposed with undecimated wavelet transform. Each sub-band is divided into(More)
Hazelnuts with damaged or cracked shells are more prone to infection with aflatoxin producing molds (Aspergillus Flavus). These molds can cause cancer. In this study, we introduce a new approach that separates damaged/cracked hazelnut kernels from good ones by using time-frequency features obtained from impact acoustic signals in an offline step. The(More)
In this paper, we propose a method for detection of small moving objects in video. We first eliminate the camera motion using motion compensation. We then use an adaptive predictor to estimate the current pixel using neighboring pixels in the motion compensated image and, in this way, obtain a residual error image. Small moving objects appear as outliers in(More)
For the registration of multi modal images some commonly used techniques are region based [1], moment based [2], region and feature based [3] and cross-correlation and FFT based [4] methods. Scale Invariant Future Transform (SIFT) is a recent, effective and popular feature based technique [5] and it has largely replaced the well-known Förstner, Harris and(More)
BACKGROUND Subtraction of ictal and interictal single photon emission computed tomography (SPECT) images is known to be successful in localizing the seizure focus in the pre-surgical evaluation of patients with partial epilepsy. A computer-aided methods for producing subtraction ictal SPECT co-registered to the magnetic resonance image (MRI) (the SISCOM(More)