Skip to Main content Skip to Navigation
New interface
Journal articles

A new collaborative classification process for microcalcification detection based on graphs and knowledge propagation

Abstract : In this paper, we propose a new collaborative process that aims to detect macrocalcifications from mammographic images while minimizing false negative detections. This process is made up of three main phases: suspicious area detection, candidate object identification, and collaborative classification. The main concept is to operate on the entire image divided into homogenous regions called superpixels which are used to identify both suspicious areas and candidate objects. The collaborative classification phase consists in making the initial results of different microcalcification detectors collaborate in order to produce a new common decision and reduce their initial disagreements. The detectors share the information about their detected objects and associated labels in order to refine their initial decisions based on those of the other collaborators. This refinement consists of iteratively updating the candidate object labels of each detector following local and contextual analyses based on prior knowledge about the links between super pixels and macrocalcifications. This process iteratively reduces the disagreement between different detectors and estimates local reliability terms for each super pixel. The final result is obtained by a conjunctive combination of the new detector decisions reached by the collaborative process. The proposed approach is evaluated on the publicly available INBreast dataset. Experimental results show the benefits gained in terms of improving microcalcification detection performances compared to existing detectors as well as ordinary fusion operators.
Complete list of metadata

https://hal-imt-atlantique.archives-ouvertes.fr/hal-03683796
Contributor : Pierre-Henri Conze Connect in order to contact the contributor
Submitted on : Tuesday, May 31, 2022 - 9:56:46 PM
Last modification on : Thursday, August 18, 2022 - 3:40:26 PM

Identifiers

Citation

Asma Touil, Karim Kalti, Pierre-Henri Conze, Basel Solaiman, Mohamed Ali Mahjoub. A new collaborative classification process for microcalcification detection based on graphs and knowledge propagation. Journal of Digital Imaging, 2022, ⟨10.1007/s10278-022-00678-9⟩. ⟨hal-03683796⟩

Share

Metrics

Record views

30