Title: On the filtering properties of classic-curvature and intensity-curvature functional images: applications in magnetic resonance imaging

Authors: Carlo Ciulla; Dimitar Veljanovski; Filip A. Risteski; Ustijana Rechkoska Shikoska

Addresses: University of Information Science and Technology, Partizanska B.B., Ohrid, 6000, Macedonia ' Department of Radiology, General Hospital 8-mi Septemvri, Boulevard 8th September, Skopje, 1000, Macedonia ' Department of Radiology, General Hospital 8-mi Septemvri, Boulevard 8th September, Skopje, 1000, Macedonia ' University of Information Science and Technology, Partizanska B.B., Ohrid, 6000, Macedonia

Abstract: Eight subjects affected from various typologies of human brain tumour were scanned using the magnetic resonance imaging (MRI) modality known as fluid attenuated inversion recovery (FLAIR). The intensity-curvature measurement approaches called: 1) classic-curvature; 2) intensity-curvature functional; were calculated when fitting to the MRI data two mathematical models: 1) the bivariate cubic polynomial; 2) the bivariate linear function, respectively. The classic-curvature and the intensity-curvature functional show well behaved medical intensity-curvature maps of the human brain and they were used as filter masks to convolve the FLAIR data. As a result of the convolution, the filtered FLAIR images were obtained and analysed searching for evidence of feature extraction. The resulting filtered FLAIR images show: 1) well behaved presentation of the tumour; 2) well behaved delineation of the parenchyma surrounding the tumour; 3) well behaved separation between the tumour and the surrounding oedema; 4) clear and neat delineation of grey and white matter of the brain. The comparison between the filtered FLAIR and the filtered T2-weighted MRI images indicates that filtering FLAIR images yields a more effective highlight of the tumour structures than filtering the T2-weighted MRI.

Keywords: fluid attenuated inversion recovery; FLAIR; magnetic resonance imaging; MRI scanning; human brain; brain tumours; classic curvature; intensity-curvature functional; ICF images; mathematical modelling; medical images; feature extraction; tumour structures.

DOI: 10.1504/IJAPR.2016.076989

International Journal of Applied Pattern Recognition, 2016 Vol.3 No.1, pp.77 - 98

Received: 02 Feb 2016
Accepted: 26 Feb 2016
Published online: 16 Jun 2016 *

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