Search results for "Image Segmentation"
showing 10 items of 234 documents
GTVcut for neuro-radiosurgery treatment planning: an MRI brain cancer seeded image segmentation method based on a cellular automata model
2018
Despite of the development of advanced segmentation techniques, achieving accurate and reproducible gross tumor volume (GTV) segmentation results is still an important challenge in neuro-radiosurgery. Nowadays, magnetic resonance imaging (MRI) is the most prominent modality in radiation therapy for soft-tissue anatomical districts. Gamma Knife stereotactic neuro-radiosurgery is a minimally invasive technology for dealing with inaccessible or insufficiently treated tumors with traditional surgery or radiotherapy. During a treatment planning phase, the GTV is generally contoured by experienced neurosurgeons and radiation oncologists using fully manual segmentation procedures on MR images. Unf…
Differential diagnostic features of bone marrow biopsies in essential thrombocythemia
2004
Essential Thrombocythemia (ET) is a chronic myeloproliferative disorder (CMPD) characterized by a high platelet count and originating from a multipotent stem cell. For a long time, according to Polycythaemia Vera Study Group (PVSG) criteria, ET diagnosis has not included histopathological data. Bone Marrow (BM) histology was used only to exclude previous or other subtypes of Ph-CMD or Myelodysplastic syndromes (MDS). In addition, the lack of any cytogenetic or molecular-biological marker has made the discrimination between ET and cases of Reactive Thrombocytosys (RT) without a well known cause quite problematic. Analogously, the distinction of ET from the other Ph- CMPDs with similar clinic…
Improving color correction across camera and illumination changes by contextual sample selection
2012
International audience; In many tasks of machine vision applications, it is important that recorded colors remain constant, in the real world scene, even under changes of the illuminants and the cameras. Contrary to the human vision system, a machine vision system exhibits inadequate adaptability to the variation of lighting conditions. Automatic white bal- ance control available in commercial cameras is not sufficient to pro- vide reproducible color classification. We address this problem of color constancy on a large image database acquired with varying digi- tal cameras and lighting conditions. A device-independent color repre- sentation may be obtained by applying a chromatic adaptation…
Color and Flow Based Superpixels for 3D Geometry Respecting Meshing
2014
We present an adaptive weight based superpixel segmentation method for the goal of creating mesh representation that respects the 3D scene structure. We propose a new fusion framework which employs both dense optical flow and color images to compute the probability of boundaries. The main contribution of this work is that we introduce a new color and optical flow pixel-wise weighting model that takes into account the non-linear error distribution of the depth estimation from optical flow. Experiments show that our method is better than the other state-of-art methods in terms of smaller error in the final produced mesh.
Karhunen-Loe`ve transform applied to region-based segmentation of color aerial images
2001
The use of the Karhunen-Loeve transform (KLT) for region- based segmentation of aerial images by color and textural attributes is presented. Our aerial images are shown to be homogeneous color im- ages within the Karhunen-Loeve color representation space, which means they can be represented more easily and the region-based seg- mentation algorithms can be optimized. For texture analysis, the KLT is the basis of the local linear transform (LLT) and allows structural infor- mation about textures to be represented in an optimal and condensed manner. The LLT provides a system of textural analysis in the form of an adapted filter bank. We end the paper by presenting a method for merg- ing textur…
A neural network based automatic road signs recognizer
2003
Automatic road sign recognition systems are aimed at detection and recognition of one or more road signs from real-world color images. In this research, road signs are detected and extracted from real world scenes on the basis of their color and shape features. A dynamic region growing technique is adopted to enhance color segmentation results obtained in the HSV color space. The technique is based on a dynamic threshold that reduces the effect of hue instability in real scenes due to external brightness variation. Classification is then performed on extracted candidate regions using multilayer perceptron neural networks. The obtained results show good detection and recognition rates of the…
Colour segmentation based on a light reflection model to locate citrus fruits for robotic harvesting
1993
Abstract Colour segmentation with a vision system is a good procedure to identify and locate fruits in robotic harvesting. Natural illumination conditions present in these environments produce a very variable illumination of the scene, in addition, fruits are usually partially occluded, and complete visual information about them is not available. The colour segmentation used for these purposes must take into account the appearance of highlights and shadows that natural illumination conditions produce. A method based on the Dichromatic Reflection Model for the light reflected from the surface object is reported here. Through the assumption of this model the light rays reflected from points o…
Low-Rate Reduced Complexity Image Compression using Directionlets
2006
The standard separable two-dimensional (2-D) wavelet transform (WT) has recently achieved a great success in image processing because it provides a sparse representation of smooth images. However, it fails to capture efficiently one-dimensional (1-D) discontinuities, like edges and contours, that are anisotropic and characterized by geometrical regularity along different directions. In our previous work, we proposed a construction of critically sampled perfect reconstruction anisotropic transform with directional vanishing moments (DVM) imposed in the corresponding basis functions, called directionlets. Here, we show that the computational complexity of our transform is comparable to the co…
SVM approximation for real-time image segmentation by using an improved hyperrectangles-based method
2003
A real-time implementation of an approximation of the support vector machine (SVM) decision rule is proposed. This method is based on an improvement of a supervised classification method using hyperrectangles, which is useful for real-time image segmentation. The final decision combines the accuracy of the SVM learning algorithm and the speed of a hyperrectangles-based method. We review the principles of the classification methods and we evaluate the hardware implementation cost of each method. We present the combination algorithm, which consists of rejecting ambiguities in the learning set using SVM decision, before using the learning step of the hyperrectangles-based method. We present re…
Learning spatial filters for multispectral image segmentation.
2010
International audience; We present a novel filtering method for multispectral satel- lite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments car- ried out on multiclass one-against-all classification and tar- get detection show the capabilities of the learned spatial fil- ters.