Hierarchical Cluster Analysis to Aid Diagnostic Image Data Visualization of MS and Other Medical Imaging Modalities

SELVAN, Arul, COLE, Laura, SPACKMAN, Lynne and WRIGHT, Chris (2017). Hierarchical Cluster Analysis to Aid Diagnostic Image Data Visualization of MS and Other Medical Imaging Modalities. In: COLE, Laura, (ed.) Imaging Mass Spectrometry Methods and Protocols. Methods in Molecular Biology, 1 . Humana Press, 95-123.

Preview

PDF Hierarchical_Cluster_Analysis_to_Aid_Diagnostic_Image_Data_Visualization_of_MS_and_Other_Medical_Imaging_Modalities.pdf - Published Version All rights reserved. Download (3MB) | Preview

Abstract

Perceiving abnormal regions in the images of different medical modalities plays a crucial role in diagnosis and subsequent treatment planning. In medical images to visually perceive abnormalities’ extent and boundaries requires substantial experience. Consequently, manually drawn region of interest (ROI) to outline boundaries of abnormalities suffers from limitations of human perception leading to inter-observer variability. As an alternative to human drawn ROI, it is proposed the use of a computer-based segmenta- tion algorithm to segment digital medical image data. Hierarchical Clustering-based Segmentation (HCS) process is a generic unsupervised segmentation process that can be used to segment dissimilar regions in digital images. HCS process generates a hierarchy of segmented images by partitioning an image into its constituent regions at hierarchical levels of allowable dissimilarity between its different regions. The hierarchy represents the continuous merging of similar, spatially adjacent, and/or disjoint regions as the allowable threshold value of dissimilarity between regions, for merging, is gradually increased. This chapter discusses in detail first the implementation of the HCS process, second the implementa- tion details of how the HCS process is used for the presentation of multi-modal imaging data (MALDI and MRI) of a biological sample, third the implementation details of how the process is used as a perception aid for X-ray mammogram readers, and finally the implementation details of how it is used as an interpreta- tion aid for the interpretation of Multi-parametric Magnetic Resonance Imaging (mpMRI) of the Prostate.

Item Type:	Book Section
Uncontrolled Keywords:	Segmentation visualisation Mass Spectrometry x-ray mammogram Magnetic Resonance Imaging Prostate
Research Institute, Centre or Group - Does NOT include content added after October 2018:	Materials and Engineering Research Institute > Engineering Research
Departments - Does NOT include content added after October 2018:	Faculty of Science, Technology and Arts > Department of Engineering and Mathematics
Page Range:	95-123
Depositing User:	Arul Selvan
Date Deposited:	07 Jun 2017 10:17
Last Modified:	18 Mar 2021 16:16
URI:	https://shura.shu.ac.uk/id/eprint/15710

Actions (login required)

View Item

Downloads

Publication Metrics