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
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
A leukocyte image fast scanning method based on max min distance clustering is proposed.Because of the lower proportion and uneven distribution of leukocytes in human peripheral blood,there will not be any leukocyte i...A leukocyte image fast scanning method based on max min distance clustering is proposed.Because of the lower proportion and uneven distribution of leukocytes in human peripheral blood,there will not be any leukocyte in lager quantity of the captured images if we directly scan the blood smear along an ordinary zigzag scanning routine with high power(100^(x))objective.Due to the larger field of view of low power(10^(x))objective,the captured low power blood smear images can be used to locate leukocytes.All of the located positions make up a specific routine,if we scan the blood smear along this routine with high power objective,there will be definitely leukocytes in almost all of the captured images.Considering the number of captured images is still large and some leukocytes may be redundantly captured twice or more,a leukocyte clustering method based on max-min distance clustering is developed to reduce the total number of captured images as well as the number of redundantly captured leukocytes.This method can improve the scanning eficiency obviously.The experimental results show that the proposed method can shorten scanning time from 8.0-14.0min to 2.54.0 min while extracting 110 nonredundant individual high power leukocyte images.展开更多
Blood cell counting is an important medical test to help medical staffs diagnose various symptoms and diseascs.An automatic segmentation of complex overlapping erythrocytes based on seed prediction in microscopic imag...Blood cell counting is an important medical test to help medical staffs diagnose various symptoms and diseascs.An automatic segmentation of complex overlapping erythrocytes based on seed prediction in microscopic imaging is proposed.The four main innovations of this ressearch are as.follows:(1)Regions of erythrocytes extracted rapidly and accurately based on the G component.(2)K-means algorithm is applied on edge detection of overlapping erythrocytes.(3)Traces of erythrocytes'biconcave shape are utilized to predict erythrocyte's position in overlapping clus-ters.(4)A new automatic counting method which aims at complex overlapping erythrocytes is presented.The experimental results show that the proposed method is efficient and accurate with very little running time.The average accuracy of the proposed method reaches 97.0%.展开更多
A leukocyte recognition method for human peripheral blood smear based on island-clustering texture(ICT)is proposed.By analyzing the features of the five typical classes of leukocyte images,a new ICT model is establish...A leukocyte recognition method for human peripheral blood smear based on island-clustering texture(ICT)is proposed.By analyzing the features of the five typical classes of leukocyte images,a new ICT model is established.Firstly,some feature points are extracted in a gray leukocyte image by mean-shift clustering to be the centers of islands.Secondly,the growing region is employed to create regions of the islands in which the seeds are just these feature points.These islands distribution can describe a new texture.Finally,a distinguished parameter vector of these islands is created as the ICT features by combining the ICT features with the geometric features of the leukocyte.Then the five typical classes of leukocytes can be recognized successfully at the correct recognition rate of more than 92.3%with a total sample of 1310 leukocytes.Experimental results show the feasibility of the proposed method.Further analysis reveals that the method is robust and results can provide important information for disease diagnosis.展开更多
A leukocyte segmentation method based on S component and B component images is proposed.Threshold segmentation operation is applied to get two binary images in S component and B component images.The samples used in th...A leukocyte segmentation method based on S component and B component images is proposed.Threshold segmentation operation is applied to get two binary images in S component and B component images.The samples used in this study are peripheral blood smears.It is easy tofind from the two binary images that gray values are the same at every corresponding pixels in theleukocyte cytoplasm region,but opposite in the other regions.The feature shows that "IMAGEAND"operation can be employed on the two binary images to segment the cytoplasm region ofleukocyte.By doing"IMAGE XOR"operation between cytoplasn region and nucleus region,theleukocyte segment ation can be retrieved effectively.The segmentation accuracy is evaluated by comparing the segmentation result of the proposed method with the manual segmentation by ahematologist.Experiment results show that the proposed method is of a higher segmentationaccuracy and it also performs well when leukocytes overlap_with erythrocytes.The averagesegmentation accuracy of the proposed method reaches 97.7%for segmenting five types ofleukocyte.Good segmentation results provide an important foundation for leukocytes aut omaticrecognition.展开更多
Blood smear test is the basic method of blood cytology and is also a standard medical test that can help diagnose various conditions and diseases.Morphological examination is the gold stan-dard to determine pathologic...Blood smear test is the basic method of blood cytology and is also a standard medical test that can help diagnose various conditions and diseases.Morphological examination is the gold stan-dard to determine pathological changes in blood cell morphology.In the biology and medicine automation trend,blood smears'automated management and analysis is very necessary.An online blood smear automatic microscopic image detection system has been constructed.It includes an online blood smear automatic producing part and a blood smear automatic micro-scopic image detection part.Online identity authentication is at the core of the system.The identifiers printed online always present dot matrix digit code(DMDC)whose stroke is not continuous.Considering the particularities of DMDC and the complexities of online application environment,an online identity authentication method for blood smear with heterological theory is proposed.By synthesizing the certain regional features according to the heterological theory,high identification accuracy and high speed have been guaranteed with few features required.In the experiment,the suficient correct matches bet ween the tube barcode and the identification result verified its feasibility and validity.展开更多
基金This work was supported by the 863 National Plan Foundation of China under Grant No.2007AA01Z333Special Grand National Project of China under Grant No.2009ZX02204-008.
文摘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%.
基金This work is supported by 863 National Plan Foundation of China under grant No.2007 AA01Z333.
文摘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.
基金supported by the 863 National Plan Foundation of China under Grant No.2007AA01Z333 and Special Grand National Project of China under Grant No.2009ZX02204-008.
文摘A leukocyte image fast scanning method based on max min distance clustering is proposed.Because of the lower proportion and uneven distribution of leukocytes in human peripheral blood,there will not be any leukocyte in lager quantity of the captured images if we directly scan the blood smear along an ordinary zigzag scanning routine with high power(100^(x))objective.Due to the larger field of view of low power(10^(x))objective,the captured low power blood smear images can be used to locate leukocytes.All of the located positions make up a specific routine,if we scan the blood smear along this routine with high power objective,there will be definitely leukocytes in almost all of the captured images.Considering the number of captured images is still large and some leukocytes may be redundantly captured twice or more,a leukocyte clustering method based on max-min distance clustering is developed to reduce the total number of captured images as well as the number of redundantly captured leukocytes.This method can improve the scanning eficiency obviously.The experimental results show that the proposed method can shorten scanning time from 8.0-14.0min to 2.54.0 min while extracting 110 nonredundant individual high power leukocyte images.
基金supported by the 863 National Plan Foundation of China under Grant No.2007AA01Z333 and Special Grand National Project of China under Grant No.2009ZX02204-008.
文摘Blood cell counting is an important medical test to help medical staffs diagnose various symptoms and diseascs.An automatic segmentation of complex overlapping erythrocytes based on seed prediction in microscopic imaging is proposed.The four main innovations of this ressearch are as.follows:(1)Regions of erythrocytes extracted rapidly and accurately based on the G component.(2)K-means algorithm is applied on edge detection of overlapping erythrocytes.(3)Traces of erythrocytes'biconcave shape are utilized to predict erythrocyte's position in overlapping clus-ters.(4)A new automatic counting method which aims at complex overlapping erythrocytes is presented.The experimental results show that the proposed method is efficient and accurate with very little running time.The average accuracy of the proposed method reaches 97.0%.
基金This work is supported by 863 National Plan Foundation of China under Grant No.2007 AA01Z333 and Special Grand National Project of China under Grant No.2009ZX02204-008.
文摘A leukocyte recognition method for human peripheral blood smear based on island-clustering texture(ICT)is proposed.By analyzing the features of the five typical classes of leukocyte images,a new ICT model is established.Firstly,some feature points are extracted in a gray leukocyte image by mean-shift clustering to be the centers of islands.Secondly,the growing region is employed to create regions of the islands in which the seeds are just these feature points.These islands distribution can describe a new texture.Finally,a distinguished parameter vector of these islands is created as the ICT features by combining the ICT features with the geometric features of the leukocyte.Then the five typical classes of leukocytes can be recognized successfully at the correct recognition rate of more than 92.3%with a total sample of 1310 leukocytes.Experimental results show the feasibility of the proposed method.Further analysis reveals that the method is robust and results can provide important information for disease diagnosis.
文摘A leukocyte segmentation method based on S component and B component images is proposed.Threshold segmentation operation is applied to get two binary images in S component and B component images.The samples used in this study are peripheral blood smears.It is easy tofind from the two binary images that gray values are the same at every corresponding pixels in theleukocyte cytoplasm region,but opposite in the other regions.The feature shows that "IMAGEAND"operation can be employed on the two binary images to segment the cytoplasm region ofleukocyte.By doing"IMAGE XOR"operation between cytoplasn region and nucleus region,theleukocyte segment ation can be retrieved effectively.The segmentation accuracy is evaluated by comparing the segmentation result of the proposed method with the manual segmentation by ahematologist.Experiment results show that the proposed method is of a higher segmentationaccuracy and it also performs well when leukocytes overlap_with erythrocytes.The averagesegmentation accuracy of the proposed method reaches 97.7%for segmenting five types ofleukocyte.Good segmentation results provide an important foundation for leukocytes aut omaticrecognition.
基金supported by the 863 National Plan Foundation of China under Grant No.2007AA01Z333 and Special Grand National Project of China under Grant No.2009ZX02204-008.
文摘Blood smear test is the basic method of blood cytology and is also a standard medical test that can help diagnose various conditions and diseases.Morphological examination is the gold stan-dard to determine pathological changes in blood cell morphology.In the biology and medicine automation trend,blood smears'automated management and analysis is very necessary.An online blood smear automatic microscopic image detection system has been constructed.It includes an online blood smear automatic producing part and a blood smear automatic micro-scopic image detection part.Online identity authentication is at the core of the system.The identifiers printed online always present dot matrix digit code(DMDC)whose stroke is not continuous.Considering the particularities of DMDC and the complexities of online application environment,an online identity authentication method for blood smear with heterological theory is proposed.By synthesizing the certain regional features according to the heterological theory,high identification accuracy and high speed have been guaranteed with few features required.In the experiment,the suficient correct matches bet ween the tube barcode and the identification result verified its feasibility and validity.
