This work introduces a new vision-based approach for estimating chlorophyll contents in a plant leaf using reflectance and transmittance as base parameters. Images of the top and underside of the leaf are captured. To estimate the base parameters (reflectance/transmittance), a novel optical arrangement is proposed.
View Article and Find Full Text PDFComput Methods Programs Biomed
September 2017
Background And Objectives: Despite the importance of the morphology of the sinus of Valsalva in the behavior of heart valves and the proper irrigation of coronary arteries, the study of these sinuses from medical imaging is still limited to manual radii measurements. This paper aims to present an automatic method to measure the sinuses of Valsalva on medical images, more specifically on cine MRI and Xray CT.
Methods: This paper introduces an enhanced method to automatically localize and extract each sinus of Valsalva edge and its relevant points.
Many denoising approaches extend image processing to a hyperspectral cube structure, but do not take into account a sensor model nor the format of the recording. We propose a denoising framework for hyperspectral images that uses sensor data to convert an acquisition to a representation facilitating the noise-estimation, namely the photon-corrected image. This photon corrected image format accounts for the most common noise contributions and is spatially proportional to spectral radiance values.
View Article and Find Full Text PDFObject: Although, there is no global consensus on their measurement, magnetic resonance imaging (MRI) appears to be particularly attractive for the study of the sinuses of Valsalva (SV). The purpose of this study was to automatically evaluate the SV from cine-MRI using a standardized method.
Materials And Methods: An automatic method based on mathematical morphology was elaborated to segment the aortic root from cross-sectional cine-MRI, and to detect relevant points, such as the commissures, the cusps and the centre of the SV.