Allan Felipe Fattori Alves1, Rachid Jennane2, José Ricardo Arruda de Miranda1, Carlos Clayton Macedo de Freitas3, Nitamar Abdala4, Diana Rodrigues de Pina5. 1. Instituto de Biociências de Botucatu, Departamento de Física e Biofísica, UNESP-Universidade Estadual Paulista, P.O. BOX 510, Distrito de Rubião Junior S/N, Botucatu, São Paulo, 18618-000, Brazil. 2. Laboratory I3MTO - University of Orleans, 5 Rue de Chartres, BP 6744, 45072, Orléans, France. 3. Departamento de Neurologia, Psicologia e Psiquiatria, Faculdade de Medicina de Botucatu, UNESP-Universidade Estadual Paulista, Distrito de Rubião Junior S/N, Botucatu, São Paulo, 18618-000, Brazil. 4. Departamento de Diagnóstico por Imagem, Escola Paulista de Medicina - UNIFESP, Rua Napoleão de Barros, 800, São Paulo, 04024-002, Brazil. 5. Departamento de Doenças Tropicais e Diagnóstico por Imagem, Faculdade de Medicina de Botucatu, UNESP-Universidade Estadual Paulista, Distrito de Rubião Junior S/N, Botucatu, São Paulo, 18618-000, Brazil. drpina@fmb.unesp.br.
Abstract
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.
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.
Entities:
Keywords:
Algorithms; Brain; Early diagnosis; Stroke; Tomography
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