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Dive into the research topics where Alain Tiedeu is active.

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Featured researches published by Alain Tiedeu.


IEEE Transactions on Biomedical Engineering | 2005

3-D reconstruction of microcalcification clusters using stereo imaging: algorithm and mammographic unit calibration

Christian Daul; Pierre Graebling; Alain Tiedeu; Didier Wolf

The three-dimensional (3-D) shape of microcalcification clusters is an important indicator in early breast cancer detection. In fact, there is a relationship between the cluster topology and the type of lesion (malignant or benign). This paper presents a 3-D reconstruction method for such clusters using two 2-D views acquired during standard mammographic examinations. For this purpose, the mammographic unit was modeled using a camera with virtual optics. This model was used to calibrate the acquisition unit and then to reconstruct the clusters in the 3-D space after microcalcification segmentation and matching. The proposed model is hardware independent since it is suitable for digital mammographic units with different geometries and with various physical acquisition principles. Three-dimensional reconstruction results are presented here to prove the validity of the method. Tests were first performed using a phantom with a well-known geometry. The latter contained X-ray opaque glass balls representing microcalcifications. The positions of these balls were reconstructed with a 16.25-/spl mu/m mean accuracy. This very high inherent algorithm accuracy is more than enough for a precise 3-D cluster representation. Further validation tests were carried out using a second phantom including a spherical cluster. This phantom was built with materials simulating the behavior of both mammary tissue and microcalcifications toward Xrays. The reconstructed shape was effectively spherical. Finally, reconstructions were carried out for real clusters and their results are also presented.


Digital Signal Processing | 2006

The EKT method for extraction of periodic signals from noise

J.S. Armand Eyebe Fouda; Martin Kom; Alain Tiedeu

Abstract Extracting periodic signal drowned in noise is a challenge in signal processing. Usually, to extract a message made up of several harmonics, it is necessary to have a reference periodic signal made up of as many harmonics. This requires a long processing time if harmonics are extracted one after another. The solution adopted is to simultaneously generate harmonics of the reference signal with the aid of the Dirac comb. This method however has limitations in terms of signal-to-noise ratio. In this paper, we propose a new reference signal which allows extracting the message with a better signal-to-noise ratio than that obtained using the Dirac comb.


Digital Signal Processing | 2009

Toward a group delay reduction in digital filtering

J.S. Armand Eyebe Fouda; Martin Kom; Alain Tiedeu; Samuel Domngang

Finite impulse response (FIR) filters are often used in digital signal processing applications because their linear phase properties do not introduce group delay distortion. While this property is desirable, we may also desire that the filter exhibit zero group delay to suppress the causal time offset between the input and output of the filter. We can minimize the causal delay by the use of recursive minimum phase filters but these introduce an objectionable group delay distortion. We desire both zero group delay and a nonrecursive impulse response (IR). This filter can be applied to input signals indirectly through a modified overlap and save FFT based circular convolution. The desired result is obtained in our proposed new filtering technique: the modified overlap and save method (MOSM). We accomplish this by redefining the time origin of the prototype filters impulse response by circularly shifting the response in the FFT filter time vector till the symmetry point coincides with the vectors zero index.


Signal & Image Processing : An International Journal | 2012

A COMPARATIVE EVALUATION OF TWO ALGORITHMS OF DETECTION OF MASSES ON MAMMOGRAMS

Guillaume Kom; Alain Tiedeu; Martin Kom; John Ngundam

In this paper, we implement and carry out the comparison of two methods of computer-aided-detection of masses on mammograms. The two algorithms basically consist of 3 steps each: segmentation, binarization and noise suppression using different techniques for each step. A database of 60 images was used to compare the performance of the two algorithms in terms of general detection efficiency, conservation of size and shape of detected masses.


Computers in Biology and Medicine | 2007

Automated detection of masses in mammograms by local adaptive thresholding

Guillaume Kom; Alain Tiedeu; Martin Kom


Digital Signal Processing | 2012

Texture-based analysis of clustered microcalcifications detected on mammograms

Alain Tiedeu; Christian Daul; Aude D. Kentsop; Pierre Graebling; Didier Wolf


Journal of Biomedical Science and Engineering | 2014

Chaos-Based Encryption of ECG Signals: Experimental Results

Gutenbert Kenfack; Alain Tiedeu


Computerized Medical Imaging and Graphics | 2005

Correspondences between microcalcification projections on two mammographic views acquired with digital systems

Alain Tiedeu; Christian Daul; Pierre Graebling; Didier Wolf


Itbm-rbm | 2005

Détection automatique des opacités dans les mammographies par la méthode de minimisation de la somme de l'inertie

Guillaume Kom; Alain Tiedeu; Martin Kom; C. Nguemgne; J. Gonsu


Journal of Biomedical Science and Engineering | 2014

Extracting and smoothing contours in mammograms using Fourier descriptors

Cyrille Feudjio; Alain Tiedeu; Marie-Laure Noubeg; Mihaela Gordan; Aurel Vlaicu; Samuel Domngang

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Martin Kom

University of Yaoundé I

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Guillaume Kom

École Normale Supérieure

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Pierre Graebling

Centre national de la recherche scientifique

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Didier Wolf

University of Lorraine

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Aude D. Kentsop

École Normale Supérieure

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Samuel Domngang

École Normale Supérieure

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