A State-of-the-Art Survey for Microorganism Image Segmentation Methods and Future Potential
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Ning Xu | Shouliang Qi | Shuo Chen | Yueyang Teng | Xin Zhao | Frank Kulwa | Chen Li | Bencheng Cai | N. Xu | Shouliang Qi | Yueyang Teng | Frank Kulwa | Chen Li | Xin Zhao | Bencheng Cai | Shuo Chen
[1] J J Vaquero,et al. Applying watershed algorithms to the segmentation of clustered nuclei. , 1998, Cytometry.
[2] Riries Rulaningtyas,et al. Multi patch approach in K-means clustering method for color image segmentation in pulmonary tuberculosis identification , 2015, 2015 4th International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME).
[3] S Mishra,et al. Automatic detection and classification of tuberculosis bacilli from camera-enabled smartphone microscopic images , 2016, 2016 Fourth International Conference on Parallel, Distributed and Grid Computing (PDGC).
[4] Muhamad Kamal Mohammed Amin,et al. Segmentation-Driven RetinaNet for Protozoa Detection , 2018, 2018 IEEE International Symposium on Multimedia (ISM).
[5] M. Y. Mashor,et al. Performance comparison of clustering and thresholding algorithms for tuberculosis bacilli segmentation , 2012, 2012 International Conference on Computer, Information and Telecommunication Systems (CITS).
[6] E. Bengtsson,et al. Cluster detection in cytology images using the cellgraph method , 2012, 2012 International Symposium on Information Technologies in Medicine and Education.
[7] T. W. Ridler,et al. Picture thresholding using an iterative selection method. , 1978 .
[8] M.Y. Mashor,et al. Colour Image Segmentation of Tuberculosis Bacilli in Ziehl-Neelsen-Stained Tissue Images Using Moving K-Mean Clustering Procedure , 2010, 2010 Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation.
[9] O. Babalola. Beneficial bacteria of agricultural importance , 2010, Biotechnology Letters.
[10] Tammy Riklin-Raviv,et al. Microscopy cell segmentation via adversarial neural networks , 2017, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).
[11] N. Otsu. A threshold selection method from gray level histograms , 1979 .
[12] Gabriel Cristobal,et al. Automatic identification techniques of tuberculosis bacteria , 2003, SPIE Optics + Photonics.
[13] Anne E Carpenter,et al. Applying Faster R-CNN for Object Detection on Malaria Images , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[14] João Paulo Papa,et al. Automatic Segmentation and Classification of Human Intestinal Parasites From Microscopy Images , 2013, IEEE Transactions on Biomedical Engineering.
[15] Yi Hong Wang. Research on Segmentation of Protozoan and Metazoan Image in Microscopic Examination of Activated Sludge , 2013 .
[16] N. Senthilkumaran,et al. Image Segmentation - A Survey of Soft Computing Approaches , 2009, 2009 International Conference on Advances in Recent Technologies in Communication and Computing.
[17] Gabriel Cristóbal,et al. Identification of tuberculosis bacteria based on shape and color , 2004, Real Time Imaging.
[18] Amlan Chakrabarti,et al. A Combined Algorithm for Malaria Detection from Thick Smear Blood Slides , 2015 .
[19] Tao Jiang,et al. Content-based Image Retrieval of Environmental Microorganisms Using Double-stage Optimisation-based Fusion , 2017 .
[20] Haiyong Zheng,et al. Automatic segmentation of Chaetoceros microscopic images via pixel-wise classification , 2016, OCEANS 2016 - Shanghai.
[21] Alioune Ngom,et al. Image segmentation of biofilm structures using optimal multi-level thresholding , 2011, Int. J. Data Min. Bioinform..
[22] Chen Li,et al. Shape-Based Classification of Environmental Microorganisms , 2014, 2014 22nd International Conference on Pattern Recognition.
[23] Alioune Ngom,et al. Efficient Optimal Multi-level Thresholding for Biofilm Image Segmentation , 2009, PRIB.
[24] David Dagan Feng,et al. Nuclei instance segmentation with dual contour-enhanced adversarial network , 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).
[25] Christian Scheel,et al. Contour based Split and Merge segmentation and pre-classification of zooplankton in very large images , 2015, International Conference on Computer Vision Theory and Applications.
[26] Pakaket Wattuya,et al. A New Shape Descriptor and Segmentation Algorithm for Automated Classifying of Multiple-morphological Filamentous Algae , 2019, ICCS.
[27] Michael Gadermayr,et al. Unsupervisedly Training GANs for Segmenting Digital Pathology with Automatically Generated Annotations , 2018, MIDL.
[28] Chen Li,et al. Environmental microbiology aided by content-based image analysis , 2015, Pattern Analysis and Applications.
[29] M. Y. Mashor,et al. A fast and accurate detection of Schizont plasmodium falciparum using channel color space segmentation method , 2017, 2017 5th International Conference on Cyber and IT Service Management (CITSM).
[30] Joel H. Saltz,et al. Unsupervised Histopathology Image Synthesis , 2017, ArXiv.
[31] Bahram Javidi,et al. Segmentation of 3D holographic images using bivariate jointly distributed region snake. , 2006, Optics express.
[32] P Memmolo,et al. Identification of bovine sperm head for morphometry analysis in quantitative phase-contrast holographic microscopy. , 2011, Optics express.
[33] Humaira Nisar,et al. Local adaptive approach toward segmentation of microscopic images of activated sludge flocs , 2015, J. Electronic Imaging.
[34] Jerome Yerly,et al. A two-step procedure for automatic and accurate segmentation of volumetric CLSM biofilm images. , 2007, Journal of microbiological methods.
[35] G. T. Raju,et al. Automated colour segmentation of Tuberculosis bacteria thru region growing: A novel approach , 2014, The Fifth International Conference on the Applications of Digital Information and Web Technologies (ICADIWT 2014).
[36] J. Denzler,et al. Segmentation of microorganism in complex environments , 2013, Pattern Recognition and Image Analysis.
[37] Pakaket Wattuya,et al. Automated Microalgae Image Classification , 2014, ICCS.
[38] Kim Sang-Bong,et al. Reconstruction and Elimination of Optical Microscopic Background Using Surface Fitting Method , 2001 .
[39] Eric Battenberg,et al. A System for Automatic Cell Segmentation of Bacterial Microscopy Images , 2006 .
[40] A. M. Khan,et al. Image Segmentation Methods: A Comparative Study , 2013 .
[41] M. C. Tomei,et al. "Microthrix parvicella", a filamentous bacterium causing bulking and foaming in activated sludge systems: a review of current knowledge. , 2005, FEMS microbiology reviews.
[42] Pulkit Kumar,et al. U-Segnet: Fully Convolutional Neural Network Based Automated Brain Tissue Segmentation Tool , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).
[43] Vishnu Vardhan Makkapati,et al. Segmentation and classification of tuberculosis bacilli from ZN-stained sputum smear images , 2009, 2009 IEEE International Conference on Automation Science and Engineering.
[44] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[45] Atsuo Yoshitaka,et al. Protozoa Identification using 3D Geometric Multiple Color Channel Local Feature , 2018, 2018 10th International Conference on Knowledge and Systems Engineering (KSE).
[46] Corina Pangilinan,et al. Application of Stepwise Binary Decision Classification for Reduction of False Positives in Tuberculosis Detection from Smeared Slides , 2011 .
[47] Bernd Hamann,et al. A Highly Accurate Level Set Approach for Segmenting Green Microalgae Images , 2015, 2015 28th SIBGRAPI Conference on Graphics, Patterns and Images.
[48] Pascal Vallotton,et al. Segmentation of Dense 2D Bacilli Populations , 2010, 2010 International Conference on Digital Image Computing: Techniques and Applications.
[49] Ali Selman Aydin,et al. CNN Based Yeast Cell Segmentation in Multi-modal Fluorescent Microscopy Data , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[50] Thomas Brox,et al. U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.
[51] J. Bezdek,et al. FCM: The fuzzy c-means clustering algorithm , 1984 .
[52] Lipo Wang,et al. Deep Learning Applications in Medical Image Analysis , 2018, IEEE Access.
[53] Abdul Aziz,et al. Improved Extraction of Objects from Urine Microscopy Images with Unsupervised Thresholding and Supervised U-net Techniques , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[54] Wei-bang Chen,et al. An Automated Bacterial Colony Counting System , 2008, 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008).
[55] Matthew Kyan,et al. Refining competition in the self-organising tree map for unsupervised biofilm image segmentation , 2005, Neural Networks.
[56] Federico Girosi,et al. Support Vector Machines: Training and Applications , 1997 .
[57] M.Y. Mashor,et al. Color thresholding method for image segmentation algorithm of Ziehl-Neelsen sputum slide images , 2008, 2008 5th International Conference on Electrical Engineering, Computing Science and Automatic Control.
[58] Chen Li,et al. Environmental microorganism classification using conditional random fields and deep convolutional neural networks , 2018, Pattern Recognit..
[59] D. Pryce. Sputum Film Cultures of Tubercle Bacilli: a Method for the Early Observation Of Growth. , 1941 .
[60] Scott T. Acton,et al. Bact-3D: A level set segmentation approach for dense multi-layered 3D bacterial biofilms , 2017, 2017 IEEE International Conference on Image Processing (ICIP).
[61] Roberto Cipolla,et al. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling , 2015, CVPR 2015.
[62] Y. Zhang,et al. A REVIEW ON IMAGE SEGMENTATION TECHNIQUES WITH REMOTE SENSING PERSPECTIVE , 2010 .
[63] Tao Jiang,et al. Environmental Microbiological Content-Based Image Retrieval System Using Internal Structure Histogram , 2015, CORES.
[64] Anil K. Jain,et al. Segmentation and classification of bacterial culture images , 1994 .
[65] Muhammad Khusairi Osman,et al. Segmentation of tuberculosis bacilli in Ziehl-Neelsen tissue slide images using Hibrid Multilayered Perceptron network , 2010, 10th International Conference on Information Science, Signal Processing and their Applications (ISSPA 2010).
[66] Leon Cohen,et al. Segmentation, autofocusing and signagture extraction of tuberculosis sputum images , 2002, SPIE Optics + Photonics.
[67] Hanchuan Peng,et al. Visualization and Analysis of 3D Microscopic Images , 2012, PLoS Comput. Biol..
[68] Ezzatollah Salari,et al. A new method for the segmentation of algae images using retinex and support vector machine , 2015, 2015 IEEE International Conference on Electro/Information Technology (EIT).
[69] Frank B. Dazzo,et al. Computer-Assisted Segmentation of Bacteria in Color Micrographs , 2004 .
[70] Polina Golland,et al. Resolving clustered worms via probabilistic shape models , 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.
[71] Chanho Jung,et al. Segmenting Clustered Nuclei Using H-minima Transform-Based Marker Extraction and Contour Parameterization , 2010, IEEE Transactions on Biomedical Engineering.
[72] Yunhui Liu,et al. A segmentation algorithm for Mycobacterium Tuberculosis images based on automatic-marker watershed transform , 2014, 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014).
[73] Yonathan Ferry Hendrawan,et al. Colour image segmentation for malaria parasites detection using cascading method , 2017, 2017 International Conference on Sustainable Information Engineering and Technology (SIET).
[74] Soumith Chintala,et al. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.
[75] Muhammad Burhan Khan,et al. Image segmentation of activated sludge phase contrast images using phase stretch transform. , 2018, Microscopy.
[76] Josef Kittler,et al. Threshold selection based on a simple image statistic , 1985, Comput. Vis. Graph. Image Process..
[77] P. S. Hiremath,et al. Segmentation and identification of rotavirus-A in digital microscopic images using active contour model , 2011 .
[78] M. Y. Mashor,et al. Comparison of color thresholding and global thresholding for Ziehl-Neelsen TB bacilli slide images in sputum samples , 2015, 2015 2nd International Conference on Biomedical Engineering (ICoBE).
[79] Chen Li,et al. A survey for the applications of content-based microscopic image analysis in microorganism classification domains , 2019, Artificial Intelligence Review.
[80] M. Y. Mashor,et al. Detection of mycobacterium tuberculosis in Ziehl-Neelsen stained tissue images using Zernike moments and hybrid multilayered perceptron network , 2010, 2010 IEEE International Conference on Systems, Man and Cybernetics.
[81] Franco Scarselli,et al. A Deep Learning Approach to Bacterial Colony Segmentation , 2018, ICANN.
[82] Alexei A. Efros,et al. Image-to-Image Translation with Conditional Adversarial Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[83] L O Hall,et al. Review of MR image segmentation techniques using pattern recognition. , 1993, Medical physics.
[84] D Marr,et al. Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.
[85] Chandan Chakraborty,et al. Plasmodium vivax segmentation using modified fuzzy divergence , 2011, 2011 International Conference on Image Information Processing.
[86] Trevor Darrell,et al. Fully convolutional networks for semantic segmentation , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[87] Demetri Terzopoulos,et al. Snakes: Active contour models , 2004, International Journal of Computer Vision.
[88] Aamir Saeed Malik,et al. Morphological analysis of activated sludge flocs and filaments , 2014, 2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings.
[89] Humaira Nisar,et al. Image segmentation of microscopic wastewater images using phase contrast microscopy , 2016, 2016 IEEE Conference on Systems, Process and Control (ICSPC).
[90] Chen Li,et al. Environmental Microorganism Classification Using Sparse Coding and Weakly Supervised Learning , 2015, EMR@ICMR.
[91] Marly Guimarães Fernandes Costa,et al. Automatic identification of tuberculosis mycobacterium , 2015 .
[92] X Yang,et al. Evaluation of biofilm image thresholding methods. , 2001, Water research.
[93] Guangxi Zhu,et al. Image segmentation using support vector machine , 2005, International Symposium on Multispectral Image Processing and Pattern Recognition.
[94] Gustavo Carneiro,et al. Automated Nucleus and Cytoplasm Segmentation of Overlapping Cervical Cells , 2013, MICCAI.
[95] J B Xavier,et al. Objective threshold selection procedure (OTS) for segmentation of scanning laser confocal microscope images. , 2001, Journal of microbiological methods.
[96] Stiaan Wiehman,et al. Semantic segmentation of bioimages using convolutional neural networks , 2016, 2016 International Joint Conference on Neural Networks (IJCNN).
[97] Rassoul Amirfattahi,et al. An Automated Method for Segmentation of Epithelial Cervical Cells in Images of ThinPrep , 2010, Journal of Medical Systems.
[98] Aleksandra Pizurica,et al. Edge Linking Based Method to Detect and Separate Individual C. Elegans Worms in Culture , 2008, 2008 Digital Image Computing: Techniques and Applications.
[99] Mohammad H. Moradi,et al. Low contrast sperm detection and tracking by Watershed algorithm and Particle filter , 2011, 2011 18th Iranian Conference of Biomedical Engineering (ICBME).
[100] Nicolas Roussel,et al. A Computational Model for C. elegans Locomotory Behavior: Application to Multiworm Tracking , 2007, IEEE Transactions on Biomedical Engineering.
[101] Pascal Fua,et al. Caenorhabditis Elegans Segmentation Using Texture-Based Models for Motility Phenotyping , 2014, IEEE Transactions on Biomedical Engineering.
[102] P. S. Hiremath,et al. Spiral Bacterial Cell Image Analysis using Active Contour Method , 2012 .
[103] P. S. Hiremath,et al. Digital Microscopic Image Analysis of Spiral Bacterial Cell Groups , 2011 .
[104] Dong Nie,et al. A deep framework for bacterial image segmentation and classification , 2015, BCB.
[105] W. Maneesukasem,et al. Urine sediment image segmentation based on feedforward backpropagation neural network , 2012, The 5th 2012 Biomedical Engineering International Conference.
[106] Lin Yang,et al. Deep Adversarial Networks for Biomedical Image Segmentation Utilizing Unannotated Images , 2017, MICCAI.
[107] Ida-Maria Sintorn,et al. Minimal annotation training for segmentation of microscopy images , 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).
[108] Shahab Ensafi,et al. Automatic segmentation of Leishmania parasite in microscopic images using a modified CV level set method , 2015, International Conference on Graphic and Image Processing.
[109] V. Maheshwari,et al. Image-guided fine-needle aspiration of retroperitoneal masses: The role of the cytopathologist , 2013, Journal of cytology.
[110] Chen Li,et al. Application of content-based image analysis to environmental microorganism classification , 2015 .
[111] Fang Zhou,et al. Microbial contour extraction based on edge detection , 2016, 2016 8th International Conference on Wireless Communications & Signal Processing (WCSP).
[112] Yongming Li,et al. Automatic cell nuclei segmentation and classification of breast cancer histopathology images , 2016, Signal Process..
[113] Pedro L. Rodrigues,et al. Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis elegans , 2012, Medical Imaging.
[114] Qunlan Zhou,et al. Role and functions of beneficial microorganisms in sustainable aquaculture. , 2009, Bioresource technology.
[115] O. Sertel,et al. Computer-aided Prognosis of Neuroblastoma: Detection of mitosis and karyorrhexis cells in digitized histological images , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[116] S. Jyothi,et al. A Survey on Threshold Based Segmentation Technique in Image Processing , 2014 .
[117] S. Beucher,et al. Watersheds of functions and picture segmentation , 1982, ICASSP.
[118] Sankar K. Pal,et al. A review on image segmentation techniques , 1993, Pattern Recognit..
[119] Manjunath Hiremath,et al. Automated Identification and Classification of Rotavirus-A Particle in Digital Microscopic Images , 2010 .
[120] Tahsin Kurc,et al. Towards building computerized image analysis framework for nucleus discrimination in microscopy images of diffuse glioma , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[121] Jean-Baptiste Sibarita,et al. Automatic non-parametric capsid segmentation using wavelets transform and graph , 2012, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI).
[122] Hala H. Zayed,et al. Remote Computer-Aided Breast Cancer Detection and Diagnosis System Based on Cytological Images , 2014, IEEE Systems Journal.
[123] Verónica Vilaplana,et al. Articulated Motion and Deformable Objects , 2018, Lecture Notes in Computer Science.
[124] Anil K. Jain. Data clustering: 50 years beyond K-means , 2008, Pattern Recognit. Lett..
[125] Marly G. F. Costa,et al. Automatic identification of mycobacterium tuberculosis with conventional light microscopy , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[126] Tao Jiang,et al. A Brief Review for Content-Based Microorganism Image Analysis Using Classical and Deep Neural Networks , 2018, ITIB.
[127] Koon Chun Lai,et al. Segmentation Approach Towards Phase-Contrast Microscopic Images of Activated Sludge to Monitor the Wastewater Treatment. , 2017, Microscopy and microanalysis : the official journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada.
[128] S E Reichenbach,et al. Evaluation of automated threshold selection methods for accurately sizing microscopic fluorescent cells by image analysis , 1989, Applied and environmental microbiology.
[129] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[130] Nancy Hitschfeld-Kahler,et al. Gold-standard and improved framework for sperm head segmentation , 2014, Comput. Methods Programs Biomed..
[131] Alioune Ngom,et al. Biofilm Image Segmentation Using Optimal Multi-level Thresholding , 2009, 2009 IEEE International Conference on Bioinformatics and Biomedicine.
[132] E. Priya,et al. Separation of overlapping bacilli in microscopic digital TB images , 2015 .
[133] Song Li,et al. An improved algorithm of rat sperm image segmentation and counting , 2010, 2010 International Conference on Intelligent Computing and Integrated Systems.
[134] Enrico Macii,et al. Automated segmentation of tissue images for computerized IHC analysis , 2022 .
[135] B. Castaneda,et al. An adaptive filtering approach for segmentation of tuberculosis bacteria in Ziehl-Neelsen sputum stained images , 2015, 2015 Latin America Congress on Computational Intelligence (LA-CCI).
[136] Fernand Meyer. Automatic screening of cytological specimens , 1986 .
[137] W. R. Sam Emmanuel,et al. An efficient approach to sputum image segmentation using improved fuzzy local information C means clustering algorithm for tuberculosis diagnosis , 2017, 2017 International Conference on Inventive Computing and Informatics (ICICI).
[138] Klaus H. Maier-Hein,et al. Adversarial Networks for the Detection of Aggressive Prostate Cancer , 2017, ArXiv.
[139] Humaira Nisar,et al. Iterative region based Otsu thresholding of bright-field microscopic images of activated sludge , 2016, 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES).
[140] Camille Couprie,et al. Semantic Segmentation using Adversarial Networks , 2016, NIPS 2016.
[141] John F. Canny,et al. A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[142] King-Sun Fu,et al. A survey on image segmentation , 1981, Pattern Recognit..
[143] Tsuyoshi Kato,et al. Virus Particle Detection by Convolutional Neural Network in Transmission Electron Microscopy Images , 2018, Food and Environmental Virology.
[144] W. R. Sam Emmanuel,et al. Segmentation and classification of mycobacterium from ziehl neelsen stained sputum images for tuberculosis diagnosis , 2017, 2017 International Conference on Communication and Signal Processing (ICCSP).