• Transactions on Control, Automation and Systems Engineering
• /
• v.4 no.3
• /
• pp.224-230
• /
• 2002

In this paper, a counting algorithm hybridized with an adaptive automatic thresholding method based on Otsu's method and the algorithm that elongates markers obtained by the well-known watershed algorithm is proposed to enhance the exactness of the microcell counting in microscopic images. The proposed counting algorithm can be stated as follows. The transformed full image captured by CCD camera set up at microscope is divided into cropped images of m$\times$n blocks with an appropriate size. The thresholding value of the cropped image is obtained by Otsu's method and the image is transformed into binary image. The microbial cell images below prespecified pixels are regarded as noise and are removed in tile binary image. The smoothing procedure is done by the area opening and the morphological filter. Watershed algorithm and the elongating marker algorithm are applied. By repeating the above stated procedure for m$\times$n blocks, the m$\times$n segmented images are obtained. A superposed image with the size of 640$\times$480 pixels as same as original image is obtained from the m$\times$n segmented block images. By labeling the superposed image, the counting result on the image of microbial cells is achieved. To prove the effectiveness of the proposed mettled in counting the microbial cell on the image, we used Acinetobacter sp., a kind of ammonia-oxidizing bacteria, and compared the proposed method with the global Otsu's method the traditional watershed algorithm based on global thresholding value and human visual method. The result counted by the proposed method shows more approximated result to the human visual counting method than the result counted by any other method.

• Journal of Biomedical Engineering Research
• /
• v.27 no.3
• /
• pp.125-130
• /
• 2006

The number of the living endothelial cells and the shape of those are very import clinical parameters for the evaluation of the quality of cornea. In this paper, we developed the automated endothelial cell counting and shape analysis algorithm for a confocal microscope. Since, the endothelial images from the confocal microscope has a non-uniform illumination and low contrast between cell boundaries and cell bodies, it is very difficult to segment the cells from the endothelial images. To cope with these difficulties, we proposed the new two stage image processing algorithm. At first stage algorithm, we used a high-pass filter and histogram equalization to compensate the non-uniform brightness pattern and a morphological filter and a watershed method are applied to detect the boundary of cells. From this stage, we could count the number of cells in an endothelial image. At second stage algorithm, we used a Voronoi diagram method to classify the shape of cells. This cell shape analysis and the percent of hexagonal cells are very sensitive in detecting the early endothelium damage. To evaluate the performance of the proposed system, we p개cessed seven endothelial images obtained using a confocal microscope. The proposed system correctly counted 95.5% cells and classified 92.0% of hexagonal cell shapes. This result is better than any others in this research area.

• Molecules and Cells
• /
• v.27 no.4
• /
• pp.391-396
• /
• 2009

Image-based, high-content screening assays demand solutions for image segmentation and cellular compartment encoding to track critical events - for example those reported by GFP fusions within mitosis, signalling pathways and protein translocations. To meet this need, a series of nuclear/cytoplasmic discriminating probes have been developed: DRAQ5$^{TM}$ and CyTRAK Orange$^{TM}$. These are spectrally compatible with GFP reporters offering new solutions in imaging and cytometry. At their most fundamental they provide a convenient fluorescent emission signature which is spectrally separated from the commonly used reporter proteins (e.g. eGFP, YFP, mRFP) and fluorescent tags such as Alexafluor 488, fluorescein and Cy2. Additionally, they do not excite in the UV and thus avoid the complications of compound UV-autofluorescence in drug discovery whilst limiting the impact of background sample autofluorescence. They provide a convenient means of stoichiometrically labelling cell nuclei in live cells without the aid of DMSO and can equally be used for fixed cells. Further developments have permitted the simultaneous and differential labelling of both nuclear and cytoplasmic compartments in live and fixed cells to clearly render the precise location of cell boundaries which may be beneficial for quantitative expression measurements, cell-cell interactions and most recently compound in vitro toxicology testing.

• Journal of IKEEE
• /
• v.20 no.1
• /
• pp.89-93
• /
• 2016

In this paper, we proposed SIMT based Image Signal Processor which can apply various image preprocessing algorithms and allow parallel processing of application programs such as image recognition. Conventional ISP has the hard-wired image enhancement algorithm of which the processing speed is fast, but there was difficult to optimize performance depending on various image processing algorithms. The proposed ISP improved the processing time applying SIMT architecture and processed a variety of image processing algorithms as an instruction based processor. We used Xilinx Virtex-7 board and the processing time compared to cell multicore processor, ARM Cortex-A9, ARM Cortex-A15 was reduced by about 71 percent, 63 percent and 33 percent, respectively.

• Journal of Korea Multimedia Society
• /
• v.10 no.7
• /
• pp.846-855
• /
• 2007

Significant feature extraction in cancer cell image analysis is an important process for grading cell carcinoma. In this study, we propose a method for 3D quantitative analysis of cell nuclei based upon digital image cytometry. First, we acquired volumetric renal cell carcinoma data for each grade using confocal laser scanning microscopy and segmented cell nuclei employing color features based upon a supervised teaming scheme. For 3D visualization, we used a contour-based method for surface rendering and a 3D texture mapping method for volume rendering. We then defined and extracted the 3D morphological features of cell nuclei. To evaluate what quantitative features of 3D analysis could contribute to diagnostic information, we analyzed the statistical significance of the extracted 3D features in each grade using an analysis of variance (ANOVA). Finally, we compared the 2D with the 3D features of cell nuclei and analyzed the correlations between them. We found statistically significant correlations between nuclear grade and 3D morphological features. The proposed method has potential for use as fundamental research in developing a new nuclear grading system for accurate diagnosis and prediction of prognosis.

• Journal of the Korean Institute of Telematics and Electronics D
• /
• v.36D no.2
• /
• pp.62-70
• /
• 1999

This paper introduces a possibility of a low-cost, high-resolution fingerprint sensor chip. The test chip is composed of $64{\times}256$ sensing cells(chip size : $2.7mm{\times}10.8mm$). A new detection circuit of charge sharing is proposed, which eliminates the influences of internal parasitic copacitances. This the reduced sensing-capacitor size enables a high resolution of 600dpi, using even conventional 0.6${\mu}m$ CMOS process. The partial fingerprint image captured therefrom are synthesized into a full fingerprint image with a image synthesis algorithm. The problems and possibilities of image synthesis technique are also analyzed and discussed.

• Journal of radiological science and technology
• /
• v.14 no.1
• /
• pp.61-72
• /
• 1991

In this paper, the rotating plate method extracting signal and reconstructing original image was proposed. The rotating methode has cell detector array each of which has used in the medical diagnosis X-ray photography. The major problem using the simple horizontal moving or non-moving methode is the size and number of detector cells which have the considerable affection on the sharpness and resolution of the reconstructed image. Secondary, the estimated pixel values of non-detected real points which are placed between detector cells will be the distorted pixels in the reconstructed image. Therefore, the proposed rotating plate method has the exact distribution on the uncertain pixels which were reconstructed by conventional methods to solve there problems. And then, the image using the rotated plate's cell out put signal was reconstructed on the computer simulation. The method will rotated the detector array plate to solve the reconstruction from the detector size and number of conventional methods. The result of simulation has estimated the original pixel position and 81 pixel/mm resolution which the reconsiderlation of the detector's moving orientation, the proposed method has 25 pixel/mm resolution. These results have been represented by 3-D computer graphics.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.3
• /
• pp.385-396
• /
• 1993

In this paper, a improved method of digital image analysis required in basic medical science for diagnosis of cells was proposed. The object image was the thyroid gland cell image, and the purpose was automatic discrimination of three classes cells(normal cell, follicular neoplastic cells, and papillary neoplastic cells) by difference of chromatin patterns. To segment the cell nucleus from background, the region segmentation algorithm by edge tracing was proposed. And feature parameter was obtained from discrete Fourier transformation of image. After construct a feature sample group of each cells, experiment of discrimination was executed with any verification cells. As a consequency of using features proposed in this paper, get a better recognition rate(70-90%) than previously reported papers, and this method give shape to get objectivity and fixed quantity in diagnosis of cells, The methods described in this paper be used immediately for discrimination of neoplastic cells.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.31B no.4
• /
• pp.30-39
• /
• 1994

A 1-chip high quality binarizing VLSI image processor (which has 8 bit ADC. 6 bit flash ADC, 15K standard cell, and 1K word ROM) based on 10 MIPS 16 bit DSP is implemented for FAX. This image processor(IP) performs image pre-processing. image quality improvement in copying and sending mode, and mixed image processing based on the fuzzy theory. And smoothing in sub-scan direction is applied for normal receiving mode data so the received data is enhanced like fine mode data. Each algorithm is processed with the same type of image processing window and 2-D image processing is implemented with a 1-D line buffer. The fabricated chip is applied to a FAX machine and image quality improvement is verified.

• Journal of Biomedical Engineering Research
• /
• v.15 no.4
• /
• pp.419-427
• /
• 1994

A new method of digital image analysis technique for discrimination of cancer cell was presented in this paper. The object image was the Thyroid Gland cells image that was diagnosed as normal and abnormal (two types of abnormal : follicular neoplastic cell, and papillary neoplastic cell), respectively. By using the proposed region segmentation algorithm, the cells were segmented into nucleus. The 16 feature parameters were used to calculate the features of each nucleus. As a consequence of using dominant feature parameters method proposed in this paper, discrimination rate of 91.11 % was obtained for Thyroid Gland cells.