International Journal of Advanced Computer Science and Applications
This paper proposes a new optimized method that is fast in rendering for 4D reconstruction from 2... more This paper proposes a new optimized method that is fast in rendering for 4D reconstruction from 2D medical images of human anatomy permitting their real-time refined visualization. This method uses the 3D reconstruction algorithm based on contour matching of medical image sequences and on the tessellation of recent GPU. In our framework, the construction of the low-resolution mesh that is based on contour extraction allows to create a 3D mesh without any ambiguity and exactly matches the real shape of the human anatomy. Such preliminary result is of great interest, since it permits to lead to other valuable realizations such as reducing the computation burden of basic meshes and displacement vectors. Moreover, one can achieve a very low storage memory, as well as one can ease the fast real-time 4D visualization with a high desired resolution. Hence, it is then straight forward that this study can contribute to easing the diagnosis and detection in real-time of human organs in motion damage and deterioration. Especially, 4D visualization technology that is still under development is highly important and needed for assessing some dangerously evaluative diseases, as in the case of lung diseases.
International Journal of Advanced Computer Science and Applications
The reconstruction of a 3D mesh using displacement vectors for medical images is a recent method ... more The reconstruction of a 3D mesh using displacement vectors for medical images is a recent method that allows the exploitation of modern GPUs. This method demonstrated its efficiency by accelerating 3D visualization calculations and optimizing the storage process. In fact, it is divided into two main stages. The first step is the construction of a basic mesh by applying the Marching Cubes algorithm, and the second step is the extraction of the displacement vectors, which represent the details lost in the basic mesh. In fact, the Marching Cubes algorithm used to build the basic mesh suffers from some problems that we will try to overcome in this article. These problems are summarized in the ambiguity encountered during the construction of the basic mesh in some cases. Also, the resulting basic mesh must undergo modifications, in order not to have errors of form, which requires time and memory, and which gives the end a final mesh which is not optimal and even erroneous in certain situations. Our method is based on extracting the contours of the anatomy to be reconstructed from a sequence of 2D images. Each contour will be represented by a triangle. The shape of the basic mesh will then be the result of the connection of these triangles. This strategy avoids the use of the marching cubes algorithm in the reconstruction of the basic mesh in order to overcome the problems mentioned above.
International Journal of Advanced Computer Science and Applications
This paper proposes a new optimized method that is fast in rendering for 4D reconstruction from 2... more This paper proposes a new optimized method that is fast in rendering for 4D reconstruction from 2D medical images of human anatomy permitting their real-time refined visualization. This method uses the 3D reconstruction algorithm based on contour matching of medical image sequences and on the tessellation of recent GPU. In our framework, the construction of the low-resolution mesh that is based on contour extraction allows to create a 3D mesh without any ambiguity and exactly matches the real shape of the human anatomy. Such preliminary result is of great interest, since it permits to lead to other valuable realizations such as reducing the computation burden of basic meshes and displacement vectors. Moreover, one can achieve a very low storage memory, as well as one can ease the fast real-time 4D visualization with a high desired resolution. Hence, it is then straight forward that this study can contribute to easing the diagnosis and detection in real-time of human organs in motion damage and deterioration. Especially, 4D visualization technology that is still under development is highly important and needed for assessing some dangerously evaluative diseases, as in the case of lung diseases.
International Journal of Advanced Computer Science and Applications
The reconstruction of a 3D mesh using displacement vectors for medical images is a recent method ... more The reconstruction of a 3D mesh using displacement vectors for medical images is a recent method that allows the exploitation of modern GPUs. This method demonstrated its efficiency by accelerating 3D visualization calculations and optimizing the storage process. In fact, it is divided into two main stages. The first step is the construction of a basic mesh by applying the Marching Cubes algorithm, and the second step is the extraction of the displacement vectors, which represent the details lost in the basic mesh. In fact, the Marching Cubes algorithm used to build the basic mesh suffers from some problems that we will try to overcome in this article. These problems are summarized in the ambiguity encountered during the construction of the basic mesh in some cases. Also, the resulting basic mesh must undergo modifications, in order not to have errors of form, which requires time and memory, and which gives the end a final mesh which is not optimal and even erroneous in certain situations. Our method is based on extracting the contours of the anatomy to be reconstructed from a sequence of 2D images. Each contour will be represented by a triangle. The shape of the basic mesh will then be the result of the connection of these triangles. This strategy avoids the use of the marching cubes algorithm in the reconstruction of the basic mesh in order to overcome the problems mentioned above.
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Papers by Lamyae Miara