Cerebral edema segmentation using textural feature

Chaudhari, Archana; Kulkarni, Jayant

doi:10.1016/j.bbe.2019.06.002

Artykuł - szczegóły

Tytuł artykułu

Cerebral edema segmentation using textural feature

Autorzy

Chaudhari Archana , Kulkarni Jayant

Wybrane pełne teksty z tego czasopisma

Identyfikatory

DOI

10.1016/j.bbe.2019.06.002

Warianty tytułu

Języki publikacji

Abstrakty

Diagnostic imaging provides a vital tool in detection and analysis of Brain pathologies. Magnetic resonance imaging (MRI) provides an effective means for non-invasive mapping of anatomy and pathology in the brain. Pathologies like cerebral edema and tumors can spread in different tissues in the brain and can affect cognitive and other functions in the body. Accurate segmentation is therefore a challenging task. Human Brain consists of different soft tissues. These tissues can be characterized using different textures. The work presents an automatic method for segmentation using textural feature of the MR image. The texture of MR image is exploited using the gray co-occurrence matrix (GLCM). GLCM creates a textural feature map by taking into account the spatial dependence of the pixels and its angular relationship between the neighboring cell pairs. Local entropy as second order textural feature is used to capture the texture of MR image. Entropy computes the randomness in pixel intensities and helps in defining a unique texture of edema for segmentation. The marked contrast enhancement obtained in FLAIR sequence of the MR image is captured as textural information by local entropy and GLCM combination. The proposed method obtains a definite textural signature of edema as well as tumor for threshold selection. Experiments on publically available BRATS database yields an average accuracy of 96%, specificity of 97%, sensitivity of 61%, Dice Coefficient as 50% and structural similarity index of 0.88 for edema. The proposed method demonstrates encouraging results in automatic segmentation of edema as well as tumor core.

Słowa kluczowe

magnetic resonance imaging local entropy brain segmentation gray co-occurrence matrix cerebral edema

rezonans magnetyczny segmentacja mózgu macierz współwystępowania obrzęk mózgu

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

599--612

Opis fizyczny

Bibliogr. 63 poz., rys., tab., wykr.

Twórcy

autor

Chaudhari Archana

archana.chaudhari@vit.edu

Department of Instrumentation Engineering, Vishwakarma Institute of Technology, Pune, India

autor

Kulkarni Jayant

jayant.kulkarni@vit.edu

Department of Instrumentation Engineering, Vishwakarma Institute of Technology, 666 Upper Indira Nagar, Bibwewadi, Pune 411037, India

Bibliografia

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Uwagi

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

W opisie bibliogr. brak poz. nr 51

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Identyfikator YADDA

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