title: Non-linear polynomial filters for edge enhancement of mammogram lesions.
abstract: OBJECTIVE
  Computer aided analysis of mammograms has been employed by radiologists as a vital tool to increase the precision in the diagnosis of breast cancer. The efficiency of such an analysis is dependent on the employed mammogram enhancement approach; as its major role is to yield a visually improved image for radiologists.
  
  
  METHODS
  Non-linear Polynomial Filtering (NPF) framework has been explored previously as a robust approach for contrast improvement of mammographic images. This paper presents the extension of NPF framework for sharpening and edge enhancement of mammogram lesions. Proposed NPF serves to provide enhancement of edges and sharpness of the lesion region (region-of-interest) in mammograms, in a manner to minimize the dependencies on pre-selected thresholds. In the present work, Logarithmic Image Processing (LIP) model has been employed for the purpose of improvement in visualization of mammograms based on Human Visual System (HVS) characteristics.
  
  
  RESULTS
  The proposed NPF filtering framework yields mammograms with significant improvement in contrast, edges as well as sharpness of the lesion region. The performance of the proposed approach has been validated using state-of-art objective evaluation measures (of mammogram enhancement) like Contrast Improvement Index (CII), Peak Signal-to-Noise Ratio (PSNR), Average Signal-to-Noise Ratio (ASNR) and Combined Enhancement Measure (CEM); as well as subjective evaluation by radiologists' opinions.
  
  
  CONCLUSIONS
  The proposed NPF provides a robust solution to perform noise controlled contrast as well as edge enhancement using a single filtering model. This leads to a better visualization of the fine lesion details predictive of their severity. The applicability of single filtering methodology for carrying out denoising, contrast and edge enhancement improves the worth of the overall framework.
authors.affiliation: Faculty of Electronics & Communication Engineering, Shri Ramswaroop Memorial University, Lucknow-Deva Road, UP, India; Department of Electronics and Communication Engineering, SRMGPC, Lucknow, UP, India. Electronic address: bhateja.vikrant@ieee.org.
authors.forename: Vikrant
authors.initials: V
authors.lastname: Bhateja
authors.affiliation: Faculty of Electronics & Communication Engineering, Shri Ramswaroop Memorial University, Lucknow-Deva Road, UP, India.
authors.forename: Mukul
authors.initials: M
authors.lastname: Misra
authors.affiliation: Dept. of Electrical Engineering, School of Engineering, Gautam Buddha University, Greater-Noida, UP, India.
authors.forename: Shabana
authors.initials: S
authors.lastname: Urooj
mesh_terms: D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D005260:Female; D006801:Humans; D007089:Image Enhancement; D008327:Mammography; D017711:Nonlinear Dynamics
keywords: Edge enhancement; Human Visual System (HVS); Logarithmic Image Processing (LIP); Mammogram lesions; Non-linear polynomial filters (NPF).