Breast Component Adaptive Wavelet Enhancement for Soft-Copy Display of Mammograms

نویسندگان

  • Spyros Skiadopoulos
  • Anna Karahaliou
  • Filippos Sakellaropoulos
  • George Panayiotakis
  • Lena Costaridou
چکیده

A method that performs multiresolution enhancement, adaptive to breast components, for optimal visualization of the entire breast area is presented. The method includes an edge detection step to distinguish breast area from mammogram background and employs Gaussian mixture modeling to segment breast components (uncompressed fat, fat and dense). The original image is decomposed using a redundant discrete wavelet transform and magnitude coefficients corresponding to each breast component are linearly mapped for contrast enhancement. Coefficient mapping is controlled by a gain factor provided by the parameters of the modeled breast components. The processed image is derived by reconstruction of the modified wavelet coefficients. The algorithm is compared with two enhancement methods proposed for soft-copy display, in a dataset of 68 mammograms containing lesions. The proposed method demonstrates increased performance in accentuating lesions embedded in fatty or dense parenchyma, as well as in visualization of anatomical features in the entire breast area.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Contrast Enhancement of Mammograms for Rapid Detection of Microcalcification Clusters

Introduction Breast cancer is one of the most common types of cancer among women.  Early detection of breast cancer is the key to reducing the associated mortality rate. The presence of microcalcifications clusters (MCCs) is one of the earliest signs of breast cancer. Due to poor imaging contrast of mammograms and noise contamination, radiologists may overlook some diagnostic signs, specially t...

متن کامل

Contrast Enhancement Using Wavelet Transform and Adaptive Denoising in Mammograms

Breast cancer is a dangerous disease for women worldwide. X-ray mammograms are typically used by radiologists for diagnosis of early-stage breast cancer to reduce the risk of mortality. In many cases they are not easy to be analyzed because mammograms are low contrast and very noisy. This paper proposes improved contrast enhancement and adaptive denoising in mammograms. First, mammograms are de...

متن کامل

Contrast Enhancement of Mammograms for Rapid Detection of Microcalcification Clusters

Introduction Breast cancer is one of the most common types of cancer among women. Early detection of breast cancer is the key to reducing the associated mortality rate. The presence of microcalcifications clusters (MCCs) is one of the earliest signs of breast cancer. Due to poor imaging contrast of mammograms and noise contamination, radiologists may overlook some diagnostic signs, specially th...

متن کامل

Designing an Algorithm for Cancerous Tissue Segmentation Using Adaptive K-means Cluttering and Discrete Wavelet Transform

Background: Breast cancer is currently one of the leading causes of death among women worldwide. The diagnosis and separation of cancerous tumors in mammographic imagesrequire accuracy, experience and time, and it has always posed itself as a major challenge to the radiologists and physicians. Objective: This paper proposes a new algorithm which draws on discrete wavelet transform and adaptive ...

متن کامل

A wavelet based mammographic system

Mammography's role in the ABSTRACT: detection of breast cancer at early stages is well known. Although more accurate than other existing techniques, mammography still only finds 80 to 90 percent of breast cancers. It has been suggested that mammograms, as normally viewed, display only about 3% of the total information detected. The general inability to detect small tumors and other salient feat...

متن کامل

ذخیره 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 نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006