Ischemic stroke enhancement using a variational model and the expectation maximization method.

Objectives: In order to enable less experienced physicians to reliably detect early signs of stroke, A novel approach was proposed to enhance the visual perception of ischemic stroke in non-enhanced CT.Methods: A set of 39 retrospective CT scans were used, divided into 23 cases of acute ischemic str...

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Publicado en:European Radiology Vol. 28; no. 9; pp. 3936 - 3943
Autores principales: Alves, Allan Felipe Fattori, Jennane, Rachid, de Miranda, José Ricardo Arruda, de Freitas, Carlos Clayton Macedo, Abdala, Nitamar, de Pina, Diana Rodrigues
Formato: Journal Article
Publicado: Springer Nature Sep2018
Acceso en línea:Ver este registro en EBSCOhost
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        atl: Ischemic stroke enhancement using a variational model and the expectation maximization method.
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          Alves, Allan Felipe Fattori
          Jennane, Rachid
          de Miranda, José Ricardo Arruda
          de Freitas, Carlos Clayton Macedo
          Abdala, Nitamar
          de Pina, Diana Rodrigues
        affil: Instituto de Biociências de Botucatu, Departamento de Física e Biofísica, UNESP—Universidade Estadual Paulista, P.O. BOX 510, Distrito de Rubião Junior S/N, 18618-000, Botucatu, São Paulo, Brazil
      sug:
        subj:
          Tomography, X-Ray Computed Methods
          Radiographic Image Interpretation, Computer-Assisted Methods
          Stroke
          Cerebral Ischemia
          Sensitivity and Specificity
          Middle Age
          Algorithms
          Retrospective Design
          Aged
          NIH Stroke Scale
          Scales
          Middle Aged: 45-64 years
          Aged: 65+ years
      ab: Objectives: In order to enable less experienced physicians to reliably detect early signs of stroke, A novel approach was proposed to enhance the visual perception of ischemic stroke in non-enhanced CT.Methods: A set of 39 retrospective CT scans were used, divided into 23 cases of acute ischemic stroke and 16 normal patients. Stroke cases were obtained within 4.5 h of symptom onset and with a mean NIHSS of 12.9±7.4. After selection of adjunct slices from the CT exam, image averaging was performed to reduce the noise and redundant information. This was followed by a variational decomposition model to keep the relevant component of the image. The expectation maximization method was applied to generate enhanced images.Results: We determined a test to evaluate the performance of observers in a clinical environment with and without the aid of enhanced images. The overall sensitivity of the observer's analysis was 64.5 % and increased to 89.6 % and specificity was 83.3 % and increased to 91.7 %.Conclusion: These results show the importance of a computational tool to assist neuroradiology decisions, especially in critical situations such as the diagnosis of ischemic stroke.Key Points: • Diagnosing patients with stroke requires high efficiency to avoid irreversible cerebral damage. • A computational algorithm was proposed to enhance the visual perception of stroke. • Observers' performance was increased with the aid of enhanced images.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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