Comparing the performance of image enhancement methods to detect microcalcification clusters in digital mammography

Mammography is the primary imaging technique for detection and diagnosis of breast cancer; however, the contrast of a mammogram image is often poor, especially for dense and glandular tissues. In these cases the radiologist may miss some diagnostically important microcalcifications. In order to improve diagnosis of cancer correctly, image enhancement technology is often used to enhance the image and help radiologists. This paper presents a comparative study in digital mammography image enhancement based on four different algorithms: wavelet-based enhancement [Asymmetric Daubechies of order 8], Contrast-Limited Adaptive Histogram Equalization [CLAHE], morphological operators and unsharp masking. These algorithms have been tested on 114 clinical digital mammography images. The comparison for all the proposed image enhancement techniques was carried out to find out the best technique in enhancement of the mammogram images to detect microcalcifications. For evaluation of performance of image enhancement algorithms, the Contrast Improvement Index [CII] and profile intensity surface area distribution curve quality assessment have been used after any enhancement. The results of this study have shown that the average of CII is about 2.61 for wavelet and for CLAHE, unsharp masking and morphology operation are about 2.047, 1.63 and 1.315 respectively. Experimental results strongly suggest that the wavelet transformation can be more effective and improve significantly overall detection of the Computer-Aided Diagnosis [CAD] system especially for dense breast. Compare to other studies, our method achieved a higher CII

Normal values of thyroid gland in Isfahan, an iodine replete area

Because of different values of thyroid volume in different populations, and the effects of different trace element and geographic substances on thyroid volume, we decided to evaluate thyroid volume and its determinants using ultrasound in healthy adults of Isfahan, a centrally located city in Iran, an iodine replete area. In a cross-sectional study, 1500 healthy adults were enrolled by cluster sampling. Serum TSH level and morning urine iodine level were measured. Thyroid exam was performed according to WHO criteria and history of previous or present thyroid disease was taken. If all the mentioned results were normal they were considered clinically normal. One third of these normal subjects referred for thyroid ultrasonography. If ultrasonography of thyroid parenchyma texture was normal, and there was no nodule by sonography [thyroid incidentaloma], thyroid volume was measured using ellipsoid formula [XxYxZx[PI]/6]. Correlation between thyroid volume and age, sex, BMI, TSH level and urinary iodine concentration [UIC] was determined by Pearson correlation coefficient, t-Test and Kolmogorov-Smirnov. Thyroid volume more than 97% of this population was considered as goiter sonographically. Data expressed asonean +/- SD, unless otherwise stated. We finally studied 200 subjects [123 Males, 77 females, average age: 37.27 +/- 11.80 Years]. The overall thyroid volume was 9.53 +/- 3.68 ml. Males thyroid volume [10.73 +/- 3.44 ml] was significantly higher than the females one [7.71 +/- 2.63 ml] [P<0.001]. The thyroid volume ranges were 3-23.9 ml, 3.6-23.9 ml and 3-14.3 ml in all, males and females, respectively. Thyroid volume values more than 97 percentile of this reference range were 10.14 ml, 11.48 ml and 8.37 ml in all, males and females respectively, and were considered goiter sonographically. Thyroid volume had a positive correlation with age [r = 0.163, P = 0.022], but did not have correlation with serum TSH, UIC, and BMI, in both sexes. There was a strong correlation between thyroid volume, and height and body surface area [r = 0.48, P<0.001]. It was documented that thyroid volume is higher in male sex and increases with age, and have a positive correlation with body surface area and height