Sharif Digital Repository

Analyzing the features of the chromosomes can be very useful for diagnosis of many genetic disorders or prediction of the possible abnormalities that may occur in the future generations. For this purpose, karyotype is often used which to make it, there is necessary to identify each one of the 24 chromosomes from the microscopic images. Definition and extraction of the morphological and band pattern based features for each chromosome is the first step to identify them. An important class of the morphological features is the location of the chromosome's centromere. Thus, centromere localization is an initial step in designing an automatic karyotyping system. In this paper, a novel algorithm... 

Vivid banding pattern of the chromosome image is a crucial part for diagnosis in karyotype medical test. Furthermore, thriving computer aided segmentation and classification depend on the initial image quality. In this paper, we propose an adaptive and iterative histogram matching algorithm for chromosome contrast enhancement especially in banding patterns which is one of the most important information laid in chromosome image. Objective histogram, with which the initial image needs to be matched, is created based on processes on the initial image histogram. Calculation of statistical moments of image histogram and determination of parameters in each step of iteration based on these moments... 

Vivid banding patterns in medical images of chromosomes are a vital feature for karyotyping and chromosome classification. The chromosome image quality may be degraded by many phenomenon such as staining, sample defectness and imaging conditions. Thus, an image enhancement processing algorithm is needed before classification of chromosomes. In this paper, we propose an adaptive and iterative histogram matching (AIHM) algorithm for chromosome contrast enhancement especially in banding patterns. The reference histogram, with which the initial image needs to be matched, is created based on some processes on the initial image histogram. Usage of raw information in the histogram of initial image...