Shared Information-Based Late Fusion for Four Mammogram Views Retrieval using Data-driven Distance Selection

Amira Jouirou, Abir Baâzaoui, Walid Barhoumi, Walid Barhoumi

2021

Abstract

Content-Based Mammogram Retrieval (CBMR) represents the most effective method for the breast cancer diagnosis, especially CBMR based on the fusion of different mammogram views. In this work, an efficient four-view CBMR method is proposed in order to further improve the mammogram retrieval performance. The proposed method consists in combining the retrieval results of the provided four views from the screening mammography, which are the Medio-Lateral Oblique (MLO) and the Cranio-Caudal (CC) views of the Left (LMLO and LCC) and the Right (RMLO and RCC) breasts. In order to personalize each query view in the final result, a classified mammogram dataset has been used to retrieve the relevant mammograms to the query. Indeed, the proposed method takes as input four query views corresponding to the four different views (LMLO, LCC, RMLO and RCC) and displays the most similar mammogram cases to each breast view using a dynamic data-driven distance selection and the shared information. In particular, we explore the use of random forest machine learning in order to predict the most appropriate similarity measure to each query view and the late fusion from the four view result-level, through the shared information concept, for the final retrieval. According to their clinical cases, the retrieved mammograms can be analyzed in order to help radiologists to make the right decision relatively to the four-view mammogram query. The reported experimental results from the challenging Digital Database for Screening Mammography (DDSM) dataset proved the effectiveness of the proposed four-view CBMR method.

Paper Citation

in Harvard Style

Jouirou A., Baâzaoui A. and Barhoumi W. (2021). Shared Information-Based Late Fusion for Four Mammogram Views Retrieval using Data-driven Distance Selection. In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP; ISBN 978-989-758-488-6, SciTePress, pages 144-155. DOI: 10.5220/0010261701440155

in Bibtex Style

@conference{visapp21,
author={Amira Jouirou and Abir Baâzaoui and Walid Barhoumi},
title={Shared Information-Based Late Fusion for Four Mammogram Views Retrieval using Data-driven Distance Selection},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP},
year={2021},
pages={144-155},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010261701440155},
isbn={978-989-758-488-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021) - Volume 4: VISAPP
TI - Shared Information-Based Late Fusion for Four Mammogram Views Retrieval using Data-driven Distance Selection
SN - 978-989-758-488-6
AU - Jouirou A.
AU - Baâzaoui A.
AU - Barhoumi W.
PY - 2021
SP - 144
EP - 155
DO - 10.5220/0010261701440155
PB - SciTePress