M. Benjelloun - Academia.edu (original) (raw)

Papers by M. Benjelloun

The Journal of Biomedical Research

Journal of Magnetic Resonance Imaging

Computers

The process of image retrieval presents an interesting tool for different domains related to comp... more The process of image retrieval presents an interesting tool for different domains related to computer vision such as multimedia retrieval, pattern recognition, medical imaging, video surveillance and movements analysis. Visual characteristics of images such as color, texture and shape are used to identify the content of images. However, the retrieving process becomes very challenging due to the hard management of large databases in terms of storage, computation complexity, temporal performance and similarity representation. In this paper, we propose a cloud-based platform in which we integrate several features extraction algorithms used for content-based image retrieval (CBIR) systems. Moreover, we propose an efficient combination of SIFT and SURF descriptors that allowed to extract and match image features and hence improve the process of image retrieval. The proposed algorithms have been implemented on the CPU and also adapted to fully exploit the power of GPUs. Our platform is pr...

International journal of computer assisted radiology and surgery, Jan 22, 2018

This study aims to provide and optimize a performing algorithm for predicting the breast cancer r... more This study aims to provide and optimize a performing algorithm for predicting the breast cancer response rate to the first round of chemotherapy using Magnetic Resonance Imaging (MRI). This provides an early recognition of breast tumor reaction to chemotherapy by using the Parametric Response Map (PRM) method. PRM may predict the breast cancer response to chemotherapy by analyzing voxel-by-voxel temporal intra-tumor changes during one round of chemotherapy. Indeed, the tumor recognizes intra-tumor changes concerning its vascularity, which is an important criterion in the present study. This method is mainly based on spatial image affine registration between the breast tumor MRI volumes, acquired before and after the first cycle of chemotherapy, and region growing segmentation of the tumor volume. To evaluate our method, we used a retrospective study of 40 patients provided by a collaborating institute. PRM allows a color map to be created with the percentages of positive, negative a...

Proceedings of the Third International Conference on Bio-inspired Systems and Signal Processing

This paper describes a new method for cervical vertebra segmentation in digitized X-ray images. W... more This paper describes a new method for cervical vertebra segmentation in digitized X-ray images. We propose a segmentation approach based on Active Shape Model method whose main advantage is that it uses a statistical model. This model is created by training it with sample images on which the boundaries of the object of interest are annotated by an expert. The specialist knowledge is very useful in this context. This model represents the local statistics around each landmark. Our application allows the manipulation of a vertebra model. The results obtained are very promising.

International Journal of Imaging, 2014

Lecture Notes in Computer Science, 2000

In this article, we are interested in the X-rays images of the spinal column in various positions... more In this article, we are interested in the X-rays images of the spinal column in various positions. The purpose of this work is to extract some parameters determining the vertebral mobility and its variation during flexion-extension movements. A modified Discrete Dynamic Contour Model (DDCM) using the Canny edge detector was the starting point for our segmentation algorithm. To address the

2006 International Conference on Image Processing, 2006

ABSTRACT This paper describes a new method of segmentation and identification of individual verte... more ABSTRACT This paper describes a new method of segmentation and identification of individual vertebrae in medical images. The final goal of the application is to determine vertebrae motion induced by their movement between two or several positions. For that, X-ray images of the spinal columns are analysed in order to extract vertebrae contours. We present a new image segmentation approach based on a preliminary selection of vertebrae regions. We use these regions information to identify each individual vertebra by its contour. For the edge detection task, we propose a polar signature representation of the contour using the image gradient of each region. After this, we apply an edge closing method exploiting polynomial fitting

International Machine Vision and Image Processing Conference (IMVIP 2007), 2007

ABSTRACT This paper describes a new segmentation approach used for detecting the location and the... more ABSTRACT This paper describes a new segmentation approach used for detecting the location and the orientation of the cervical spinal column in medical X-ray images. A first preprocessing step consists on determining a global polygonal region for each vertebra. After this, we propose two different methods to calculate vertebrae orientation. The first method is based on the four faces detection of each vertebra contour when the second is essentially based on automatic corners localization. A specific goal of the proposed application is to create an efficient semi-automated method of identifying the overall spine curvature and the orientation angles of each vertebra. The final goal is to determine vertebrae motion induced by their movement between two or several positions.

Handbook of Research on ICTs and Management Systems for Improving Efficiency in Healthcare and Social Care, 2013

ABSTRACT In this chapter, the authors propose a new method belonging to content medical-based ima... more ABSTRACT In this chapter, the authors propose a new method belonging to content medical-based image retrieval approaches and that uses a set of region-based shape descriptors. The search engine discussed in this work allows the classification of newly acquired medical images into some well known categories and also to get the images that are more similar to a query image. The final goal is to help the medical staff to annotate these images. To achieve this task, the authors propose a set of three descriptors that are based on: (1) Hu, (2) Zernike moments, and (3) Fourier transform-based signature, which are considered as region descriptors. The advantage of using this kind of global descriptor is that they are very fast, real time, and they do not need any segmentation step. The authors propose also a comparative study between these three approaches. The search engines are tested by using a database composed of 75 images that have different sizes, and that are classified into five classes. The results provided by the proposed retrieval approaches are given with high precision. The comparison between the three approaches is achieved using classification matrices and the recall/precision curves. The three proposed retrieval approaches produce accurate results in real time. This proves the advantage of using global shape features as a preliminary classification step in an automated aided diagnosis system.

this paper addresses the problem of 3D shape retrieval in large databases of 3D objects (large re... more this paper addresses the problem of 3D shape retrieval in large databases of 3D objects (large retrieval). While this problem is emerging and interesting as the size of 3D object databases grows rapidly, the main two issues the community has to focus on are: computational efficiency of 3D object retrieval and the quality of retrieved results. In this work we deal with the first consideration, namely the computational efficiency of 3D object retrieval by exploiting new implementations based on parallel computing by exploiting multi-core and GPU architectures. Experimental results, show that the large scale retrieval can be achieved using the multi-core environment.

The purpose of this study is dedicated to cervical vertebra mobility analysis in conventional rad... more The purpose of this study is dedicated to cervical vertebra mobility analysis in conventional radiography. Indeed, vertebra detection and segmentation present an essential step toward spine motion study. However, this task becomes more challenging in conventional radiography due to low contrast and noise noticed in this medical image modality. Based on our previous work on semi-automatic detection of vertebra [1], we propose in this paper a robust method for cervical vertebra body identification and segmentation in X-ray images. This new method enables to compute the parameters used for vertebra motion analysis.

2010 2nd International Conference on Image Processing Theory, Tools and Applications, 2010

ABSTRACT In this paper, we introduce a robust approach to detect points of interest in cervical s... more ABSTRACT In this paper, we introduce a robust approach to detect points of interest in cervical spine radiographs. The perspective of this work is to segment the vertebrae on X-Ray images for the analysis of the vertebral mobility. In previous work, we proposed a segmentation technique based on Active Shape Model. The extraction and the detection of the vertebra corners can contribute to the automatic initialization of the Active Shape Model search and can give valuable information about the spine curvature. Here, we present the benefits of the polygonal approximation dedicated to the points of interest detection. The methodology developed here is composed of 3 stages: a contrast limited adaptive histogram equalization, a Canny edge detection filter and an edge polygonal approximation. The first histogram equalization step is a pretraitment needed to improve the image quality in order to perform a better contour detection. The Canny operator detects the edges in the radiograph which are used as an input to the polygonal approximation. The edges become segment lines whose intersections define corners. We compare the results obtained with our approach based on the polygonal approximation to results coming from the Harris corner detector.

2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), 2012

ABSTRACT Statistical shape models are commonly used in various applications of computer vision. N... more ABSTRACT Statistical shape models are commonly used in various applications of computer vision. Nevertheless, these models are not well adapted to hierarchical structures. This paper proposes a solution to this problem by presenting a general framework to build multilevel statistical shape models. Based on multilevel component analysis, the idea is to decompose the data into a within-individual and a between-individual component. As a result, several sub-models are deduced and can be treated separately, each level characterizing one sub-model. In this paper, we present a multilevel model of the human spine. The results show that such a modelization offers more flexibility and allows deformations that classical statistical models can simply not generate.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2012

Severe cases of spinal deformities such as scoliosis are usually treated by a surgery where instr... more Severe cases of spinal deformities such as scoliosis are usually treated by a surgery where instrumentation (hooks, screws and rods) is installed to the spine to correct deformities. Even if the purpose is to obtain a normal spine curve, the result is often straighter than normal. In this paper, we propose a fast statistical reconstruction algorithm based on a general model which can deal with such instrumented spines. To this end, we present the concept of multilevel statistical model where the data are decomposed into a within-group and a between-group component. The reconstruction procedure is formulated as a second-order cone program which can be solved very fast (few tenths of a second). Reconstruction errors were evaluated on real patient data and results showed that multilevel modeling allows better 3D reconstruction than classical models.

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2007

This paper describes a new segmentation approach for detecting the location and the orientation o... more This paper describes a new segmentation approach for detecting the location and the orientation of the cervical vertebrae in medical X-ray images. A first pre-processing step consists on determining a global polygonal region for each vertebra. After this, we propose a new approach of vertebrae localization based on the four faces detection of each vertebra contour. A specific goal of the proposed application is to create an efficient semi-automated method of identifying the overall angle of curvature of the spine and the angles between vertebrae. The final goal is to determine the motion of the vertebrae induced by their movement between two or several positions.

Intelligent Decision Support, 1992

Asilomar Conference on Signals, Systems & Computers, 1999

We present a 3D dynamic reconstruction method based on the point representation of a segment usin... more We present a 3D dynamic reconstruction method based on the point representation of a segment using sequences of images. Our vision system delivers at every time, two images of the scene: an intensity image and a range image. This estimation problem is solved by a global filter that matches the segments through the sequences of intensity and range images, and