Mammogram synthesis using a 3D simulation. II. Evaluation of synthetic mammogram texture.
نویسندگان
چکیده
We have evaluated a method for synthesizing mammograms by comparing the texture of clinical and synthetic mammograms. The synthesis algorithm is based upon simulations of breast tissue and the mammographic imaging process. Mammogram texture was synthesized by projections of simulated adipose tissue compartments. It was hypothesized that the synthetic and clinical texture have similar properties, assuming that the mammogram texture reflects the 3D tissue distribution. The size of the projected compartments was computed by mathematical morphology. The texture energy and fractal dimension were also computed and analyzed in terms of the distribution of texture features within four different tissue regions in clinical and synthetic mammograms. Comparison of the cumulative distributions of the mean features computed from 95 mammograms showed that the synthetic images simulate the mean features of the texture of clinical mammograms. Correlation of clinical and synthetic texture feature histograms, averaged over all images, showed that the synthetic images can simulate the range of features seen over a large group of mammograms. The best agreement with clinical texture was achieved for simulated compartments with radii of 4-13.3 mm in predominantly adipose tissue regions, and radii of 2.7-5.33 and 1.3-2.7 mm in retroareolar and dense fibroglandular tissue regions, respectively.
منابع مشابه
A Suruliandi and G Murugeswari: Empirical Evaluation of Lbp and Its Derivates for Abnormality Detection in Mammogram Images
Digital image processing techniques are useful in abnormality detection in mammogram images. Recently, texture based image segmentation of mammogram images has become popular due to its better precision and accuracy. Local Binary Pattern has been a recently proposed texture descriptor which attracted the research community rigorously towards texture based analysis of digital images. Many textur...
متن کاملDecide, Detect and Classify Benign and Malignant in Mammograms Using Cv-partitioning Method
In recent years, the stage determining and classifying the mammogram as Benign or Malignant is somewhat complicated process in the medical research. In the earlier papers many classification techniques, CAD designs and feature extraction methods are used constantly for mammogram classification, and has its own advantages and limitations. To overcome the limitations, in this paper a novel approa...
متن کاملBreast abnormalities segmentation using the wavelet transform coefficients aggregation
Introduction: Breast cancer is the most common cancer among women in the world. The automatic detection of masses in digital mammograms is a challenging task and a major step in the development of breast cancer CAD systems. In this study, we introduce a new method for automatic detection of suspicious mass candidate (SMC) regions in a mammogram. Methods: Mammography is widely used for the early...
متن کاملTextural Feature Extraction and Classification of Mammogram Images using CCCM and PNN
This work presents and investigates the discriminatory capability of contourlet coefficient cooccurrence matrix features in the analysis of mammogram images and its classification. It has been revealed that contourlet transform has a remarkable potential for analysis of images representing smooth contours and fine geometrical structures, thus suitable for textural details. Initially the ROI (Re...
متن کاملComputer Aided Classification of Architectural Distortion in Mammograms Using Texture Features
Computer aided diagnosis systems provide vital opinion to radiologists in the detection of early signs of breast cancer from mammogram images. Architectural distortions, masses and microcalcifications are the major abnormalities. In this paper, a computer aided diagnosis system has been proposed for distinguishing abnormal mammograms with architectural distortion from normal mammogram. Four typ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Medical physics
دوره 29 9 شماره
صفحات -
تاریخ انتشار 2002