Multi-modality GLCM image texture feature for segmentation and tissue classification

Diego Andrade; Howard C. Gifford; Mini Das

doi:10.1117/12.2659078

7 April 2023 Multi-modality GLCM image texture feature for segmentation and tissue classification

Diego Andrade, Howard C. Gifford, Mini Das

Proceedings Volume 12463, Medical Imaging 2023: Physics of Medical Imaging; 124634P (2023) https://doi.org/10.1117/12.2659078
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Conference Poster

Abstract

Humans and computer observer models often rely on feature analysis from a single imaging modality. We will examine benefits of new features that assist in image classification and detection of malignancies in MRI and X-Ray tomographic images. While the image formation principles are different in these modalities, there are common features like contrast that are often employed by humans (radiologist) in each of these when making decision. We will examine other features that may not be well-understood or explored such as grey level co-occurrence matrix (GLCM) texture features. As preliminary data, we show here the utility of some of these features along with classification methods aided by Gaussian mixture models (GMM) and fuzzy C-Means dimensionality reduction. GLCM maps characterize the image texture and provide a numerical and spatial tool of the texture signatures present in it. We will present pathways for using these in tissue classification, segmentation and development of task-based assessments.

Citation Download Citation

Diego Andrade, Howard C. Gifford, and Mini Das "Multi-modality GLCM image texture feature for segmentation and tissue classification", Proc. SPIE 12463, Medical Imaging 2023: Physics of Medical Imaging, 124634P (7 April 2023); https://doi.org/10.1117/12.2659078

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