A NEW STRATEGY FOR AUTOMATIC BREAST CANCER SEGMENTATION IN MRI IMAGES

automatic segmentation; Breast cancer; expectation-maximization algorithm; MRI; tumor detection; Automatic segmentations; Breast Cancer; Breast tumour; Cardiovascular disease; Diagnosis planning; Expectations maximization algorithms; Imaging modality; MRI Image; Treatment planning; Tumour detection; Biomedical Engineering

Abstract :

[en] Breast tumor is one of the causes of women's death in the world after cardiovascular diseases. Recently, the diagnosis and treatment planning of this kind of tumors are based on magnetic resonance imaging techniques, which are the reference imaging modality in breast tumors analysis since it can better differentiate soft tissues (compared to mammography and ultrasound). Segmentation of the breast cancer is a very important task for cancer response prediction in neoadjuvant chemotherapy treatment based either on texture analysis or parametric response maps. In most of the previous works in the literature, the segmentation is generally done with manual annotation of tumor regions, which is time-consuming and error-prone. In this paper, we propose a new strategy for an automatic segmentation of breast tumors in MRI images. We propose first to separate the two breasts, and then, we use the Expectation-Maximization Algorithm to segment and detect the tumor lesion.

Disciplines :

Computer science

Author, co-author :

Ammar, Mohammed; Engineering Systems and Telecommunication Laboratory, University m'Hamed Bougara, Boumerdes, Algeria

Mahmoudi, Saïd ; Université de Mons - UMONS > Faculté Polytechnique > Service Informatique, Logiciel et Intelligence artificielle

Language :

English

Title :

A NEW STRATEGY FOR AUTOMATIC BREAST CANCER SEGMENTATION IN MRI IMAGES

Publication date :

August 2022

Journal title :

Journal of Mechanics in Medicine and Biology

ISSN :

0219-5194

Publisher :

World Scientific

Volume :

Issue :

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

https://www.worldscientific.com/doi/pdf/10.1142/S0219519422500555

Research institute :

R300 - Institut de Recherche en Technologies de l'Information et Sciences de l'Informatique
R450 - Institut NUMEDIART pour les Technologies des Arts Numériques

Available on ORBi UMONS :

since 13 January 2023

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