Literature DB >> 17072580

"Hippocrates-mst": a prototype for computer-aided microcalcification analysis and risk assessment for breast cancer.

George Spyrou1, Smaragda Kapsimalakou, Antonis Frigas, Konstantinos Koufopoulos, Stamatios Vassilaros, Panos Ligomenides.   

Abstract

One of the most common cancer types among women is breast cancer. Regular mammographic examinations increase the possibility for early diagnosis and treatment and significantly improve the chance of survival for patients with breast cancer. Clustered microcalcifications have been considered as important indicators of the presence of breast cancer. We present "Hippocrates-mst", a prototype system for computer-aided risk assessment of breast cancer. Our research has been focused in developing software to locate microcalcifications on X-ray mammography images, quantify their critical features and classify them according to their probability of being cancerous. A total of 260 cases (187 benign and 73 malignant) have been examined and the performance of the prototype is presented through receiver operating characteristic (ROC) analysis. The system is showing high levels of sensitivity identifying correctly 98.63% of malignant cases.

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Year:  2006        PMID: 17072580     DOI: 10.1007/s11517-006-0117-2

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  39 in total

1.  Parameter optimization of a computer-aided diagnosis scheme for the segmentation of microcalcification clusters in mammograms.

Authors:  Marios A Gavrielides; Joseph Y Lo; Carey E Floyd
Journal:  Med Phys       Date:  2002-04       Impact factor: 4.071

Review 2.  Mammography and computerized decision systems: a review.

Authors:  Antônio C Roque; Túlio C S S André
Journal:  Ann N Y Acad Sci       Date:  2002-12       Impact factor: 5.691

3.  Computer-Aided Diagnosis of Breast Cancer on Mammograms.

Authors: 
Journal:  Breast Cancer       Date:  1997-12-25       Impact factor: 4.239

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Authors:  M Lanyi
Journal:  Radiologe       Date:  1977-05       Impact factor: 0.635

5.  Identification of clustered microcalcifications on digitized mammograms using morphology and topography-based computer-aided detection schemes. A preliminary experiment.

Authors:  Y H Chang; B Zheng; W F Good; D Gur
Journal:  Invest Radiol       Date:  1998-10       Impact factor: 6.016

6.  An improved shift-invariant artificial neural network for computerized detection of clustered microcalcifications in digital mammograms.

Authors:  W Zhang; K Doi; M L Giger; R M Nishikawa; R A Schmidt
Journal:  Med Phys       Date:  1996-04       Impact factor: 4.071

7.  Fractal modeling and segmentation for the enhancement of microcalcifications in digital mammograms.

Authors:  H Li; K J Liu; S C Lo
Journal:  IEEE Trans Med Imaging       Date:  1997-12       Impact factor: 10.048

8.  [Diagnostic value of clustered microcalcifications discovered by mammography (apropos of 227 cases with histological verification and without a palpable breast tumor)].

Authors:  M Le Gal; G Chavanne; D Pellier
Journal:  Bull Cancer       Date:  1984       Impact factor: 1.276

9.  Evaluation of an automated wavelet-based system dedicated to the detection of clustered microcalcifications in digital mammograms.

Authors:  M Lado; P G Tahoces; A J Méndez; M Souto; J J Vidal
Journal:  Med Inform Internet Med       Date:  2001 Jul-Sep

10.  Reproducibility of prompts in computer-aided detection (CAD) of breast cancer.

Authors:  C G Taylor; J Champness; M Reddy; P Taylor; H W W Potts; R Given-Wilson
Journal:  Clin Radiol       Date:  2003-09       Impact factor: 2.350

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