Social-Group-Optimization based tumor evaluation tool for clinical brain MRI of Flair/diffusion-weighted modality

• Autorzy: Dey Nilanjan , Rajinikanth V. , Shi Fuqian , Tavares João Manuel R.S. , Moraru Luminita , Arvind Karthik K. , Lin Hong , Kamalanand K. , Emmanuel C.

Identyfikatory

DOI

10.1016/j.bbe.2019.07.005

• Języki publikacji: EN

Abstrakty

EN

Brain tumor is one of the harsh diseases among human community and is usually diagnosed with medical imaging procedures. Computed-Tomography (CT) and Magnetic-Resonance- Image (MRI) are the regularly used non-invasive methods to acquire brain abnormalities for medical study. Due to its importance, a significant quantity of image assessment and decision-making procedures exist in literature. This article proposes a two-stage image assessment tool to examine brain MR images acquired using the Flair and DW modalities. The combination of the Social-Group-Optimization (SGO) and Shannon's-Entropy (SE) supported multi-thresholding is implemented to pre-processing the input images. The image post-processing includes several procedures, such as Active Contour (AC), Watershed and region-growing segmentation, to extract the tumor section. Finally, a classifier system is implemented using ANFIS to categorize the tumor under analysis into benign and malignant. Experimental investigation was executed using benchmark datasets, like ISLES and BRATS, and also clinical MR images obtained with Flair/DW modality. The outcome of this study confirms that AC offers enhanced results compared with other segmentation.

Słowa kluczowe

EN

Brain MRI; brain tumor; social group optimization; Shannon's entropy; ANFIS classifier; clinical MRI dataset

PL

MRI mózgu; guz mózgu; entropia Shannona; klasyfikator ANFIS

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2019
• Tom: Vol. 39, no. 3
• Strony: 843--856
• Opis fizyczny: Bibliogr. 69 poz., rys., tab., wykr.

Twórcy

autor

Dey Nilanjan

• Department of Information Technology, Techno India College of Technology, Kolkata 700156, West Bengal, India

autor

Rajinikanth V.

• Department of Electronics and Instrumentation Engineering, St. Joseph's College of Engineering, Chennai Tamilnadu, India

autor

Shi Fuqian

• College of Information and Engineering, Wenzhou Medical University, Wenzhou China

autor

Tavares João Manuel R.S.

• Instituto de Ciênciae Inovaçãoem Engenharia Mecânicae Engenharia Industrial, Departamento de Engenharia Mecânica, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal

autor

Moraru Luminita

• Dunarea de Jos, University of Galati, Faculty of Sciences and Environment, Department of Chemistry, Physics and Environment, 47 Galati, Romania

autor

Arvind Karthik K.

• Managing Director and Radiologist, Proscan Diagnostics Private Limited, Chennai Tamilnadu, India

autor

Lin Hong

• Department of Computer Science and Engineering Technology, University of Houston-Downtown, Houston, Texas USA

autor

Kamalanand K.

• Department of Instrumentation Engineering, MIT Campus, Anna University, Chennai Tamilnadu, India

autor

Emmanuel C.

• Gleneagles Global Health City, Perumbakkam, Chennai Tamilnadu, India

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Uwagi

PL

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).