Retinal OCT Texture Analysis for Differentiating Healthy Controls from Multiple Sclerosis (MS) with/without Optic Neuritis.

Multiple sclerosis (MS) is an inflammatory disease damaging the myelin sheath in the central and peripheral nervous system in the brain and spinal cord. Optic Neuritis (ON) is one of the most prevalent ocular demonstrations of MS. The current diagnosis protocol for MS is MRI, but newer modalities li...

Descripción completa

Detalles Bibliográficos
Publicado en:BioMed Research International pp. 1 - 14
Autores principales: Tazarjani, Hamidreza Dehghan, Amini, Zahra, Kafieh, Rahele, Ashtari, Fereshteh, Sadeghi, Erfan
Formato: algorithm diagnostic images equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 7/22/2021
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=151522999&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 151522999
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        23146133
        FT2T
      jtl: BioMed Research International
      issn: 23146133
      maglogo: N
    pubinfo:
      dt: 7/22/2021
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
    artinfo:
      ui:
        151522999
        151522999
        151522999
        10.1155/2021/5579018
        151522999
      ppf: 1
      ppct: 13
      formats:
        fmt:
          @attributes:
            type: P
      tig:
        atl: Retinal OCT Texture Analysis for Differentiating Healthy Controls from Multiple Sclerosis (MS) with/without Optic Neuritis.
      aug:
        au:
          Tazarjani, Hamidreza Dehghan
          Amini, Zahra
          Kafieh, Rahele
          Ashtari, Fereshteh
          Sadeghi, Erfan
        affil: Medical Image and Signal Processing Research Center, School of Advanced Technologies in Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
      sug:
        subj:
          Multiple Sclerosis Diagnosis
          Tomography, Optical Coherence
          Optic Neuritis
          Human
          Diagnostic Imaging Methods
          Comparative Studies
          Predictive Value of Tests
      ab: Multiple sclerosis (MS) is an inflammatory disease damaging the myelin sheath in the central and peripheral nervous system in the brain and spinal cord. Optic Neuritis (ON) is one of the most prevalent ocular demonstrations of MS. The current diagnosis protocol for MS is MRI, but newer modalities like Optical Coherence Tomography (OCT) are already of interest in early detection and progression analysis. OCT reveals the symptoms of MS in the Central Nervous System (CNS) through cross-sectional images from neural retinal layers. Previous works on OCT were mostly focused on the thickness of retinal layers; however, texture features seem also to have information in this regard. In this research, we introduce a new pipeline that constructs layer-stacked (LS) images containing data from each specific layer. A variety of texture features are then extracted from LS images to differentiate between healthy controls and ON/None-ON MS cases. Furthermore, the definition of texture extraction methods is tailored for this application. After performing a vast survey on available texture analysis methods, a treasury of powerful features is collected in this paper. As a primary work, this paper shows the ability of such features in the diagnosis of HC and MS (ON and None-ON) cases. Our findings show that the texture features are powerful to diagnose MS cases. Furthermore, adding information of conventional thickness values to texture features improves considerably the discrimination between most of the target groups including HC vs. MS, HC vs. MS-None-ON, and HC vs. MS-ON.
      pubtype: Academic Journal
      doctype:
        algorithm
        diagnostic images
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N