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Tumor detection in MRI brain images based on saliency computational modeling

Research output: Chapter in Book/Report/Conference proceedingConference contribution

In recent years, the issue of tumor detection for Magnetic Resonance Imaging (MRI) brain images has become a research hotspot in the field of medical imaging, multimedia and pattern recognition. In this paper, we propose a tumor detection method based on saliency modeling for MRI brain images. Firstly, in order to overcome the influence of the skull, we utilize the morphological method to strip the skull of the MRI brain images. Then, we introduce a principal local contrast based saliency-detection method to enhance the foreground regions which facilitates to get the leision region. Finally, the results are further improved by denoising, segmentation and morphological operations. Experiments performed on MRI brain images show that the proposed method is useful and effective.
Original languageEnglish
Title of host publicationThe 3rd IFAC Conference on Cyber-Physical & Human-Systems
PublisherInstitute of Electrical and Electronics Engineers
Publication statusAccepted for publication - 6 Oct 2020
EventThe 3rd IFAC Workshop on Cyber-Physical & Human Systems - Beijing, China
Duration: 3 Dec 20205 Dec 2020

Conference

ConferenceThe 3rd IFAC Workshop on Cyber-Physical & Human Systems
CountryChina
CityBeijing
Period3/12/205/12/20

Documents

  • Tumor Detection in MRI Brain Images Based on Saliency_pp

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    Accepted author manuscript (Post-print), 747 KB, PDF document

    Due to publisher’s copyright restrictions, this document is not freely available to download from this website until: 1/01/50

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