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Deep learning has been applied to saliency detection in recent years. The superior performance has proved that deep networks can model the semantic properties of salient objects. Yet it is difficult for a deep network to discriminate pixels belonging to similar receptive fields around the object boundaries, thus deep networks may output maps with blurred saliency and inaccurate boundaries. To tackle...
Due to the very low contrast between the microorganisms and background in sewage microscopic images, few traditional segmentation algorithms are available to extract the object contours from surrounding environment completely and smoothly. In this paper, we propose a novel contour extraction method for microorganisms in sewage micro-images. Firstly, Sobel operator is utilized to calculate the image...
This paper proposed a new full automated detection algorithm for ultrasound follicle images. The proposed algorithm uses multiple concentric layers (MCL) technology, which is based on the presence of concentric layers surrounding a focal area in the follicle region. The algorithm experiment is based on three processes, which include image preprocessing, detection of focal areas and multiple concentric...
It is difficult to accurately forecast the arriving time of the tidal bore on the Qiantang River, and the destroying of the tidal bore is huge. For above issues, this paper proposes the tide line detection based on image. With this method, we can accurately predict the tide bore, and then reduce casualty incidents. This method mainly includes the extraction of the tide line and the tidal warning strategy,...
Since the properties of temporal and spatial complexity and mass diversity that remote sensing image data owns, remote sensing image retrieval becomes an international advanced frontier scientific issue in remote sensing. Content-based image retrieval technology is currently widely used; however, the difference between low-level features and high-level semantics, named semantic gap, becomes a difficult...
The study is to investigate a fast globally convex variational model for the multiphase image segmentation. Firstly, a nonconvex energy functional on the membership functions, which are used as indicators of different homogeneous regions, is introduced by incorporating edge-based information. Secondly, the nonconvex problem is converted into a continuous convex formulation. Finally, a dual minimization...
The study is to investigate a fast multiphase image segmentation model from a statistical framework. The globally convex image segmentation method and the split Bregman method are incorporated into the model by maximizing the posterior image densities over all possible partitions of the image plane. The proposed model is robust with respect to noise based on Gaussian kernel function and can avoid...
The Kleihauer–Betke (KB) test is the standard method for quantitating fetal-maternal hemorrhage in maternal care. In hospitals, the KB test is performed by a certified technologist to count a minimum of 2000 fetal and maternal red blood cells (RBCs) on a blood smear. Manual counting suffers from inherent inconsistency and unreliability. This paper describes a system for automated counting and distinguishing...
Cryo-electron microscopy (CryoEM) is a very important method for studying the structures of macromolecules. Segmentation is one of the key problems in CryoEM technique. We propose a new 3D watershed, where marching cube is employed as a marker method to control the segmentation. It can transform the domain knowledge into watershed by an interactive interface with iso surface, by which we avoid over-segmentation...
Correct mass diagnosis in mammogram can reduce the unnecessary biopsy without increasing false negatives. In this paper, we investigated the usage of random forest classifier for the classification of masses with geometry and texture features. Before extracting features, the mass regions need to be extracted. Based on the initial contour guided by radiologist, level set segmentation is used to deform...
In this paper, an automatically method for mass detection was introduced, which combines multiple layers concentric (MLC) and narrow band region-based active contour (NBAC) technique. We used an improved level set method to segment the mass for contour refinement, after the boundary of a mass is found, texture features from Gray Level Cooccurrence Matrix (GLCM) are extracted from the surrounding area...
In this paper, we investigate the classification of masses with texture features. We propose an improved level set method to find the boundary of a mass, based on the initial contour provided by radiologists. After the boundary of a mass is found, texture features from Gray Level Co-occurrence Matrix (GLCM) are extracted from the surrounding area of the boundary of the mass. The extracted texture...
In this paper, a review of man-made object detection algorithms is presented based on various fractal features which are derived from the blanket covering method. These fractal features include fractal dimension (D), fractal model fitting error (FE), D-dimension area (K), multi-scale fractal feature related with D (MFFD), and multi-scale fractal feature related with K (MFFK). To choose the optimal...
The finite element method (FEM) geometry modeling of realistic head volume conductor plays an important role in FEM-based EEG/MEG forward and inverse problems. In this paper, a tetrahedron mesh generation method was developed for finite element modeling of human head. By using this method, a finite element model of human head is obtained from segmented medical images, and tested in application to...
The finite element (FE) modeling of a realistic head is a key issue for the finite element analysis of brain electromagnetic field. In the present study, we have developed a new method to generate subject specific FE head models based on their magnetic resonance (MR) and computer tomography (CT) imaging data. The present approach consists of three parts: segmentation of MR and CT images, co-registration...
Noise reduction is an important image processing method which has wide applications in different fields. The key to noise reduction is to reduce the noise without deteriorating the important features in the images. Anisotropic diffusion filter is one of the methods which satisfy this need and draws much attention from researchers in the past. However, traditional anisotropic diffusion filter has many...
The FEM geometry modeling of realistic head is a key issue for the research on FEM-based EEG/MEG. In this paper, a methodology is developed to construct this kind of model. By using this method, a five -layer realistic head FEM model is obtained, and with its application in FEM-based EEG, a satisfying result shows the reliability of the model
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