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New approaches for Contrast enhancement of calcifications in mammography using morphological enhancement

Published: 23 November 2015 Publication History

Abstract

The mammography is the technique of imagery the most used to detect tumors at an early stage; it is currently the most sensitive method for early detection of breast cancer. Our work aims to provide a computer-aided detection (CAD) system that can help radiology specialists in the interpretation of mammogram for screening breast calcifications. For this purpose, we propose to use a system for the detection of calcifications, based on a new approach suggested for enhancing the contrast of mammography image. The latter is based on the suppression of noise (to decrease the noise to the maximum) by a Gaussian filter in order to bring out all the spots (Clear Spots) possible to be calcifications; by using an operator of the Top-Hat transform. This hat is resulting from the mathematical morphology, which make it possible to keep only these small structures. Visually, the obtained results are very clear, and show the good performance of the new approach suggested in this work. These latter allows extracting successfully the calcifications starting from the mammography referents from the mini-MIAS database [1].

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  1. New approaches for Contrast enhancement of calcifications in mammography using morphological enhancement

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      cover image ACM Other conferences
      IPAC '15: Proceedings of the International Conference on Intelligent Information Processing, Security and Advanced Communication
      November 2015
      495 pages
      ISBN:9781450334587
      DOI:10.1145/2816839
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 23 November 2015

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      Author Tags

      1. Top-Hat transform
      2. breast cancer
      3. calcification
      4. filters Gaussian
      5. mammography
      6. mathematical morphology

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      • (2024)Augmented reality aid in diagnostic assistance for breast cancer detectionMultimedia Tools and Applications10.1007/s11042-024-18979-2Online publication date: 27-Mar-2024
      • (2024)Advancing mammography breast mass detection through diffusion segmentationMultimedia Tools and Applications10.1007/s11042-024-18840-6Online publication date: 27-Mar-2024
      • (2022)Brain Tumor Segmentation on MRI using a GVF Snake Model2022 7th International Conference on Image and Signal Processing and their Applications (ISPA)10.1109/ISPA54004.2022.9786335(1-5)Online publication date: 8-May-2022
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