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Analyzing high-resolution images of astrocytes is important in understanding the diseases, such as glaucoma and retinal detachment, to which astrocytes are known to become reactive. This is challenging because the cells are small, homogeneous, and closely packed. We propose an interactive visualization system designed for such images. Our system employs a probabilistic segmentation algorithm to help...
In this work, we introduce a computational approach that automatically detects stained follicles in IHC-stained follicular lymphoma slides using various biomarkers. This novel approach is to process whole-slide and Giga-byte scaled pathology images at multi-resolution levels. The average segmentation accuracy achieves at 83.09±6.25%. Such a computerized analysis of images is expected to provide a...
This paper describes a new method developed for fusion of X-ray and fluorescent molecular tomography (FMT) images. For easier diagnostics, images obtained from X-ray and FMT sources are fused to generate perceptibly informative image display using the spatial and spectral domain properties of the images. The basic premise in this research originates from the fact that in medical imaging not all the...
Automated segmentation of pigmented skin lesions (PSLs) from dermoscopy images is an important step for computer-aided diagnosis of skin cancer. The segmentation task involves classifying each image pixel as either lesion or skin. It is challenging because lesion and skin can often have similar appearance. We present a novel exemplar-based algorithm for lesion segmentation which leverages the context...
We present a methodology for the automatic identification and delineation of germ-layer components in H&E stained images of teratomas derived from human and nonhuman primate embryonic stem cells. A knowledge and understanding of the biology of these cells may lead to advances in tissue regeneration and repair, the treatment of genetic and developmental syndromes, and drug testing and discovery...
We present nonparametric methods for segmenting and classifying stem cell nuclei so as to enable the automatic monitoring of stem cell growth and development. The approach is based on combining level set methods, multiresolution wavelet analysis, and non-parametric estimation of the density functions of the wavelet coefficients from the decomposition. Additionally, to deal with small size textures...
Diabetic retinopathy is a major cause of blindness. Earliest signs of diabetic retinopathy are damage to blood vessels in the eye and then the formation of lesions in the retina. This paper presents an automated method for the detection of bright lesions (exudates) in retinal images. In this work, an adaptive thresholding based on a novel algorithm for pure splitting of the image is proposed. A coarse...
This paper presents a novel object-oriented stereo matching on multi-scale superpixels to generate a low-resolution depth map. It overcomes the classic downsampling methods' disadvantages, such as boundary blurring, outlier enlargement and foreground objects merging to background, etc. The approach we exploited is to segment the image in three scales' superpixels from dense to sparse ones according...
Tonsillitis disease is the cause of heart attack and pneumonia. It is also a sign of suspected symptom of heart disease. To improve data transfer rates, this paper proposes VLSI architecture by using color model for early-state tonsillitis detection. In this method, input image is divided into 9 blocks. Each block has 3times3 window which send color data and pixel address to computation box. The system...
This paper describes an automatic technique for the segmentation, detection and quantification of bacilli and clusters present in a digital image of sputum smear samples prepared with the Ziehl-Neelsen technique. Algorithms for color space segmentation, quantification and automatic diagnosis are described. Different color spaces (RGB, HSV,YIQ, YCbCr, Lab) were considered in order to develop and algorithm...
The following topics are dealt with: image coding; medical image processing; image reconstruction; image segmentation; image retrieval; image color analysis; image resolution; image motion analysis; face recognition; image sequences; and edge detection.
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