Skip to Main content Skip to Navigation
Journal articles

Automatic detection of microcalcification based on morphological operations and structural similarity indices

Asma Touil 1, 2 Karim Kalti 1 Pierre-Henri Conze 2, 3 Basel Solaiman 2 Mohamed Ali Mahjoub 1
1 LATIS - Laboratory of Advanced Technology and Intelligent Systems
2 IMT Atlantique - ITI - Département lmage et Traitement Information
3 LaTIM - Laboratoire de Traitement de l'Information Medicale
Abstract : In this paper, a new method for automatic detection of microcalcifications in digitized mammograms is proposed. Based on mathematical morphology theory to deal with the problem of low contrast between microcalcifications and their surrounding pixels, it uses various structuring elements of different sizes to reduce the sensibility to microcalcification diversity sizes. The obtained morphological results are converted to a suspicion map based on an image quality assessment metric called structural similarity index (SSIM). This continuous map is, then, locally analyzed using superpixels to automatically estimate threshold values and finally detect potential microcalcification areas. The proposed method was evaluated using the publicly-available INBreast dataset. Experimental results show the benefits gained in terms of improving microcalcification detection performances compared to state-of-the-art methods.
Keywords : mammography breast cancer microcalcification detection mathematical morphology structural similarity index
Document type :
Journal articles
Complete list of metadatas
https://hal-imt-atlantique.archives-ouvertes.fr/hal-02563861
Contributor : Pierre-Henri Conze <>
Submitted on : Tuesday, May 5, 2020 - 4:16:10 PM
Last modification on : Friday, January 8, 2021 - 10:05:42 PM

Identifiers

Collections

IMT-ATLANTIQUE | UNIV-BREST | LATIM | IBSAM | INSTITUT-TELECOM

Citation

Asma Touil, Karim Kalti, Pierre-Henri Conze, Basel Solaiman, Mohamed Ali Mahjoub. Automatic detection of microcalcification based on morphological operations and structural similarity indices. Biocybernetics and Biomedical Engineering, 2020, 40 (3), pp.1155-1173. ⟨10.1016/j.bbe.2020.05.002⟩. ⟨hal-02563861⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

81