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A counting method for complex overlapping erythrocytes-based microscopic imaging 被引量:1
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作者 Xudong Wei Yiping Cao +1 位作者 guangkai fu Yapin Wang 《Journal of Innovative Optical Health Sciences》 SCIE EI CAS 2015年第6期25-35,共11页
Red blood cell(RBC)counting is a standard medical test that can help diagnose various conditions and diseases.Manual counting of blood cells is highly tedious and time consuming.However,new methods for counting blood ... Red blood cell(RBC)counting is a standard medical test that can help diagnose various conditions and diseases.Manual counting of blood cells is highly tedious and time consuming.However,new methods for counting blood cells are customary employing both electronic and computer-assisted techniques.Image segmentation is a classical task in most image processing applications which can be used to count blood cells in a microscopic image.In this research work,an approach for erythrocytes counting is proposed.We employed a classification before counting and a new segmentation idea was implemented on the complex overlapping clusters in a microscopic smear image.Experimental results show that the proposed method is of higher counting accuracy and it performs much better than most counting algorithms existed in the situation of three or more RBCs overlapping complexly into a group.The average total erythrocytes counting accuracy of the proposed method reaches 92.9%. 展开更多
关键词 Cell counting image processing image segmentation overlap erythrocyte cell classification K-MEANS
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A fast auto-focusing method of microscopic imaging based on an improved MCS algorithm 被引量:1
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作者 guangkai fu Yiping Cao Mingteng Lu 《Journal of Innovative Optical Health Sciences》 SCIE EI CAS 2015年第5期67-76,共10页
An improved"three steps"mountain-climb searching(MCS)algorithm is proposed which is applied to auto-focusing for microscopic imaging accurately and efficiently.By analyzing the performance of several evaluat... An improved"three steps"mountain-climb searching(MCS)algorithm is proposed which is applied to auto-focusing for microscopic imaging accurately and efficiently.By analyzing the performance of several evaluation functions,the variance function and the Brenner function are synthesized as a new evaluation function.In the first step,a self-adaptive step length which is much dependent on the reciprocal of the evaluation function value at the beginning position of climbing is used for approaching the halfway up the mountain roughly.Secondly,a fixed moderate step length is applied for approaching the mountaintop of the variance function as closer as possible.Finally,afine step is employed for reaching the exact mountaintop of the Brenner function.The microscope auto-focusing experiments based on the proposed algorithm for blood smear detection have been carried out comprehensively.The results show that the improved algorithm can not only guarantee the precision to get clear focal images,but also improve the auto-focusing e±ciency. 展开更多
关键词 AUTO-FOCUSING evaluation function mountain-climb searching algorithm image processing
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