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Breast cancer is the most common malignant disease in women. Mammographic mass retrieval system can help radiologists to improve the diagnostic accuracy by retrieving biopsy-proven masses which are similar with the diagnostic ones. However, although screening mammograms usually consists of two-view(MLO and CC) mammography of the same breast, most breast CAD systems incorporate with image retrieval...
The classification of breast masses into benign and malignant categories plays an important role in the area of computer-aided diagnosis (CAD) of breast cancer. In this paper, one novel scheme based on multi-view information fusion is proposed, in order to improve the accuracy and the robustness of the classification and reduce the false positive rates. Five contour and shape features of the masses...
Feature extracted from structural irregularity for skin lesion boundaries has a great significance in computer-aided diagnosis for melanomas. Based on previous work using local fractal dimension (local FD) for contour irregularity descriptions, the novelty of this paper focuses on: (1) Multi-scaled curvature analysis is used to acquire features of boundary irregularity (2) Feature differences from...
The classification of breast masses into benign and malignant categories plays an important role in the area of computer-aided diagnosis (CAD) of breast cancer. In this paper, in order to improve the accuracy and the robustness of the classification and reduce the false positive rates, we proposed one novel scheme that was based on information fusion in multi views. A series of contour and shape features...
The purpose of this study is to investigate the significance of the multi-agent interactive information fusion algorithm over the matter of identification of breast masses in digitized images. For the lack of enough correlation information between the individual classifiers, the generalization performance of the Bayesian fusion method is sometimes far from the expected level, and thereby the multi-agent...
In this work, we described a new two-stage hierarchical framework for mammogram retrieval. We tested the proposed approach on the reference library from USF-DDSM. For each query ROI (region of interest), the proposed scheme first computes its 14 texture and shape features, then the voting method based on five classifiers is used to classify the ROIs in the reference library, this phase eliminates...
Mass segmentation plays an important role in many computer-aided diagnosis (CAD) system. It is usually used as the previous step of mass classification. In this paper, we propose one novel scheme for segmentation of breast mass in digitized mammograms, which is based on gradient vector flow (GVF) snake and multi-scale analysis using Gaussian pyramid. In the proposed method, mammogram is decomposed...
Since texture describes the local information of pixels' intensity variation, which can be regarded as the non-linear signals, non-linear signal analysis methods may be applied to texture analysis. Complexity analysis, as a popular non-linear signal analysis approach, is widely used for biological and clinical data analysis. In this paper, for exploring study purpose, a two-dimensional structure complexity...
An approach of medical image decomposition and texture feature extraction based on the bidimensional empirical mode decomposition(BEMD), which can decompose the image into a set of functions denoted intrinsic mode functions (IMF) and a residue, was presented. Features extracted were the mean and standard deviation of the amplitude matrix, phase matrix and instantaneous frequency matrix of the IMFs...
Breast cancer has become one of the most dangerous tumors for middle-aged and older women in China recently. Mammography is its most reliable detection method in the clinic, and computer-aided diagnosis (CAD) could assist the radiologists in reading the mammograms. In this paper, a new algorithm was proposed to estimate the skin-line of the breast automatically, which could be divided into four steps...
Mammography is one of the most effective detection methods of breast cancer. A novel algorithm was proposed to segment the pectoral muscle automatically. It firstly carried out a series of ROIs upon the neighborhood, and in each ROI, the optimal threshold was computed with the iterative thresholding. After combining these thresholds into an optimal threshold curve and computing the corresponding local...
This paper proposes an integer-to-integer shape adaptive discrete wavelet transform(ISA-DWT) coding scheme for CT(computed tomography) image. The scheme consists of (1) extraction of shape information of the foreground of CT image; (2) integer-to-integer shape adaptive discrete wavelet transform; (3) the modified SPIHT algorithm. In CT image, the foreground contains useful clinical information and...
The development of computer-aided diagnosis (CAD) methods to improve a radiologist's decision-making in reading mammography is facing a bottle-neck problem. One critical reason is that almost all current CAD methods are actually developed to perform as an independent "reader" rather than a complementary assistant "second reader" to the radiologists. This paper proposes a new computer...
Breast cancer has become one of the most dangerous carcinomas for middle-aged and older women in China recently. Mammography is its most reliable detection method in the clinic, and computer-aided diagnosis (CAD) could assist the radiologists in reading the mammograms. In this paper, a new algorithm based on two ANNs (artificial neural networks), was proposed to detect the masses automatically. It...
A novel mass segmentation algorithm is proposed in this paper. It establishes two mass models to represent the various masses, uses iterative thresholding to extract the suspicious area, and applies a DWT-based approach to locate the masses. And then, a region growing process restricted by Canny edge detection is carried out to extract the rough mass regions, and finally active contour model is used...
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