Literature DB >> 12583572

Classification of galactograms with ramification matrices: preliminary results.

Predrag R Bakic1, Michael Albert, Andrew D A Maidment.   

Abstract

RATIONALE AND
OBJECTIVES: The poor specificity of galactography, the imaging modality generally indicated in cases of nipple discharge, has led to a large number of biopsies with negative results. A quantitative scheme for classifying galactographic findings might help reduce the number of such biopsies in the future. As a first step toward that goal, the authors have studied one quantitative method for describing the branching of ducts by using ramification matrices (R matrices), and the correlation of the values of the matrix elements with clinical findings.
MATERIALS AND METHODS: The ductal trees were manually segmented for 25 galactographic views from 15 patients, and corresponding R matrices were calculated. Patients were divided into two groups: those with no reported galactographic findings (NF) and those with reported findings (RF) of ductal ectasia, cysts, or papilloma. In a leave-one-out fashion, the authors evaluated a classification scheme that was based on R-matrix coefficients and used a Bayesian decision rule. The effects of segmentation were tested by successively removing each of the terminal ducts and computing the corresponding matrices of the pruned trees.
RESULTS: With use of a single R-matrix element, 92% and 62% of NF and RF cases were correctly classified, respectively (P = .007). With use of two elements, 83% and 77% of NF and RF cases were correctly classified, but this result was not statistically significant (P = .108). In a test of robustness, an analysis of pruned trees yielded an average root-mean-square fractional difference of 9.7% between the elements of the original and the R matrix averaged over all pruned trees.
CONCLUSION: The preliminary analysis indicates that it may be possible to identify cases with reported galactographic findings by using R matrices.

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Mesh:

Year:  2003        PMID: 12583572     DOI: 10.1016/s1076-6332(03)80045-4

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  4 in total

1.  Development and characterization of an anthropomorphic breast software phantom based upon region-growing algorithm.

Authors:  Predrag R Bakic; Cuiping Zhang; Andrew D A Maidment
Journal:  Med Phys       Date:  2011-06       Impact factor: 4.071

2.  Three-dimensional in silico breast phantoms for multimodal image simulations.

Authors:  David M Mahr; Rohit Bhargava; Michael F Insana
Journal:  IEEE Trans Med Imaging       Date:  2011-11-09       Impact factor: 10.048

3.  Analyzing tree-shape anatomical structures using topological descriptors of branching and ensemble of classifiers.

Authors:  Angeliki Skoura; Predrag R Bakic; Vasilis Megalooikonomou
Journal:  J Theor Appl Comput Sci       Date:  2013

4.  A representation and classification scheme for tree-like structures in medical images: analyzing the branching pattern of ductal trees in X-ray galactograms.

Authors:  Vasileios Megalooikonomou; Michael Barnathan; Despina Kontos; Predrag R Bakic; Andrew D A Maidment
Journal:  IEEE Trans Med Imaging       Date:  2008-08-08       Impact factor: 10.048

  4 in total

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