Acoustic resonant response of smooth or rough 3D small objects

Gavriloaia, Gheorghe; Gavriloaia, Mariuca-Roxana

doi:10.1016/j.measurement.2011.11.014

Cited by 9 publications

(4 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As an example for this filtering method, a thermal image [18,19] showing the temperature distribution on the neck area of a person suffering from papillary carcinoma is shown in Fig. 1a.…”

Section: Resultsmentioning

confidence: 99%

“…These values were imposed by the CFL condition. The iterative process begins by calculating the diffusion coefficients using the algorithm described by Gonzalez in [13,18] and the coefficient k 3 from (3). The temperature of each pixel is obtained from (2).…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, the stopping of diffusion process is very important for obtaining a good image reconstruction. Several authors attempted to devise optimal stopping criteria, such as: Weickert -the variance of the filtered image relative to the variance of the original image [14], Mrázek -minimizing the covariance of the image to the noise [15], Dolcetta and Ferretti -minimization of the performance index [16], Bazan -maximum of the second derivative of correlation between initial and current images [17,18]. We compared the temporal evolution of the thermal image filtering when the bioheat has only the conductive component, such as the algorithms proposed by Malik and Perona, Weickert, and Gonzales, with the proposed algorithm using two bioheat components: conductive and convective.…”

Section: An Improved Methods For Ir Image Filtering From Living Beingsmentioning

confidence: 99%

See 2 more Smart Citations

An improved method for IR image filtering from living beings

Gavriloaia

Vizireanu

Neamtu

et al. 2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

View full text Add to dashboard Cite

A new method to enhancing the quality of the images acquired with infrared camera is presented. Usually, thermal image filtering process relies on heat conductive component that propagates through tissue. An improved method for nonlinear filtering is presented in this article. A new component of the heat, the convection is associated heat that propagates through the tissues of living beings. From the physical point of view, this component is the result of blood flow through the tissue. The proposed algorithm uses both parts of the heat components and iteratively minimizes the noise that is added to the signal. During the iterative filtering process, the noise is more quickly minimized than other methods can do. Thermal contour shape is an important indicator for oncologists to diagnose superficial cancers such as breast, thyroid and skin. The proposed method has been tested on more patients and an example of an IR image filtering taken from a patient suffering from papillary carcinoma is shown at different iterations. The algorithm convergence speed and the contour shape are compared with the results obtained by using anisotropic filtering.

show abstract

“…As an example for this filtering method, a thermal image [18,19] showing the temperature distribution on the neck area of a person suffering from papillary carcinoma is shown in Fig. 1a.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: An Improved Methods For Ir Image Filtering From Living Beingsmentioning

confidence: 99%

See 1 more Smart Citation

An improved method for IR image filtering from living beings

Gavriloaia

Vizireanu

Neamtu

et al. 2013

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

View full text Add to dashboard Cite

show abstract

“…Like wavelet or Fourier transforms, recently, Huang proposed the Empirical Mode Decomposition method, EMD based into a set of basic functions [18,19]. These functions are derived from the signal itself and capture the repeating behavior at the same particular time scale.…”

Section: Y=pxmentioning

confidence: 99%

Remote assessment of heart rate by skin color processing

Gavriloaia

Vizireanu

Alin

et al. 2015

2015 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)

View full text Add to dashboard Cite

Oxy-hemoglobin and deoxy-hemoglobin, main blood chromatophores flowing through the arteries and veins, respectively, reflect sunlight differently. The biggest difference is at a specific wavelength in the visible spectrum. The amount of blood in the arteries varies during cardiac activity. As a result, the skin color changes, but its limits cannot be noticed in heart cycle. The authors present an algorithm, for video signal processing, to achieve remote heartbeat having the following steps: selection of the region of interest, filtering using principal component analysis and empirical mode decomposition. The proposed method uses fewer pixels than those used by other methods presented in the literature and was confirmed by testing on subjects in the room light conditions by using a pulse oximeter.

show abstract