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White blood cells nucleus segmentation from microscopic images of strained peripheral blood film during leukemia and normal condition

https://doi.org/10.1109/iciev.2016.7760026
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9781119975595.ch11openalex-snapshot
RGB Colorimetry
inferredcites →https://doi.org/10.1002/cyto.a.10106openalex-snapshot
Direct neural network application for automated cell recognition
inferredcites →https://doi.org/10.1007/978-1-84996-169-1_19openalex-snapshot
Morphological Image Processing
inferredcites →https://doi.org/10.1007/978-3-662-03939-7openalex-snapshot
Morphological Image Analysis
inferredcites →https://doi.org/10.1016/0165-1684(94)90060-4openalex-snapshot
Topographic distance and watershed lines
inferredcites →https://doi.org/10.1016/b978-0-12-372578-3.00008-8openalex-snapshot
Morphological Image Processing
inferredcites →https://doi.org/10.1108/sr.2000.08720cae.001openalex-snapshot
Morphological Image Analysis: Principles and Applications
inferredcites →https://doi.org/10.1109/ccece.2013.6567770openalex-snapshot
Chronic lymphocytic leukemia cell segmentation from microscopic blood images using watershed algorithm and optimal thresholding
inferredcites →https://doi.org/10.1109/cimsa.2005.1522835openalex-snapshot
Automatic morphological analysis for acute leukemia identification in peripheral blood microscope images
inferredcites →https://doi.org/10.1109/healthcom.2012.6379408openalex-snapshot
An enhanced threshold based technique for white blood cells nuclei automatic segmentation
inferredcites →https://doi.org/10.1109/icacci.2014.6968362openalex-snapshot
Classification of white blood cells based on morphological features
inferredcites →https://doi.org/10.1109/icaee.2014.6838448openalex-snapshot
Analysis of leukocyte blood cell for medical diagnosis using sectionalisation
inferredcites →https://doi.org/10.1109/icdcsyst.2014.6926205openalex-snapshot
Separation and counting of blood cells using geometrical features and distance transformed watershed
inferredcites →https://doi.org/10.1109/icdsp.2002.1028167openalex-snapshot
Teager energy based blood cell segmentation
inferredcites →https://doi.org/10.1109/icgccee.2014.6922219openalex-snapshot
Detection of abnormal blood cells on the basis of nucleus shape and counting of WBC
inferredcites →https://doi.org/10.1109/iciip.2011.6108977openalex-snapshot
Blood microscopic image segmentation using rough sets
inferredcites →https://doi.org/10.1109/icobe.2012.6179016openalex-snapshot
Red blood cell segmentation using masking and watershed algorithm: A preliminary study
inferredcites →https://doi.org/10.1109/icobe.2015.7235915openalex-snapshot
Color and morphological based techniques on white blood cells segmentation
inferredcites →https://doi.org/10.1109/icsmc.2009.5346736openalex-snapshot
A novel white blood cell detection method based on boundary support vectors
inferredcites →https://doi.org/10.1109/ictai.2012.133openalex-snapshot
A Fast Technique for White Blood Cells Nuclei Automatic Segmentation Based on Gram-Schmidt Orthogonalization
inferredcites →https://doi.org/10.1109/mspct.2013.6782094openalex-snapshot
An improved methodology for blood cell counting
inferredcites →https://doi.org/10.1109/tencon.2003.1273221openalex-snapshot
Automation of differential blood count
inferredcites →https://doi.org/10.1109/titb.2012.2207398openalex-snapshot
Semiautomatic White Blood Cell Segmentation Based on Multiscale Analysis
inferredcites →https://doi.org/10.1117/3.592975.p66openalex-snapshot
Photometry

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Histolab: A Python Library for Reproducible Digital Pathology Preprocessing with Automated Testing
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Review on Image Segmentation Techniques Incorporated with Machine Learning in the Scrutinization of Leukemic Microscopic Stained Blood Smear Images
inferred← citeshttps://doi.org/10.1007/978-3-031-20650-4_13openalex-snapshot
White Blood Cell Classification of Porcine Blood Smear Images
inferred← citeshttps://doi.org/10.1007/978-981-19-2057-8_10openalex-snapshot
Leukemia Detection Using Machine and Deep Learning Through Microscopic Images—A Review
inferred← citeshttps://doi.org/10.1007/978-981-19-3089-8_45openalex-snapshot
Acute Lymphocytic Leukemia Classification Using Color and Geometry Based Features
inferred← citeshttps://doi.org/10.1007/s11517-019-01984-1openalex-snapshot
Detection of acute lymphoblastic leukemia using image segmentation and data mining algorithms
inferred← citeshttps://doi.org/10.1007/s11831-019-09366-4openalex-snapshot
Computational Nuclei Segmentation Methods in Digital Pathology: A Survey
inferred← citeshttps://doi.org/10.1016/b978-0-443-21519-3.00029-7openalex-snapshot
Recent advances of microfluidic organ-on-a-chip monitoring strategies
inferred← citeshttps://doi.org/10.1109/ccip57447.2022.10058676openalex-snapshot
Image Segmentation and Counting of Red Blood Cells in Hepatitis B Patients
inferred← citeshttps://doi.org/10.1109/embc.2019.8856734openalex-snapshot
Rotation Invariant Clustering of 3D Cell Nuclei Shapes
inferred← citeshttps://doi.org/10.1109/iccic.2017.8524465openalex-snapshot
Techniques for Segmentation and Classification of Leukocytes in Blood Smear Images - A Review
inferred← citeshttps://doi.org/10.1109/iccis54243.2021.9676191openalex-snapshot
Leukocytes Segmentation and Classification in Digital Microscopic Images
inferred← citeshttps://doi.org/10.1109/iccre.2018.8376476openalex-snapshot
White blood cell classification and counting using convolutional neural network
inferred← citeshttps://doi.org/10.1109/icsp.2018.8652384openalex-snapshot
Blood Cells Counting using Python OpenCV
inferred← citeshttps://doi.org/10.1109/rbme.2020.3004639openalex-snapshot
Segmentation of White Blood Cell, Nucleus and Cytoplasm in Digital Haematology Microscope Images: A Review–Challenges, Current and Future Potential Techniques
inferred← citeshttps://doi.org/10.1109/smc.2019.8913843openalex-snapshot
A Novel Approach for Efficient Implementation of Nucleus Detection and Segmentation Using Correlated Dual Color Space
inferred← citeshttps://doi.org/10.1109/tem.2021.3103549openalex-snapshot
Peripheral Blood Smear Analysis Using Automated Computer-Aided Diagnosis System to Identify Acute Myeloid Leukemia
inferred← citeshttps://doi.org/10.1109/wiecon-ece69386.2025.11526094openalex-snapshot
Fabrication Defect Detection and Characterization of Semiconductor Devices from SEM Images Using Morphological Image Processing
inferred← citeshttps://doi.org/10.1145/3514495openalex-snapshot
Automated Analysis of Blood Smear Images for Leukemia Detection: A Comprehensive Review
inferred← citeshttps://doi.org/10.14419/ijet.v7i2.24.12068openalex-snapshot
Leukaemia Detection in Microscopic Imagery using Optimization Algorithm
inferred← citeshttps://doi.org/10.17485/ijst/2019/v12i20/145114openalex-snapshot
Detection and Segmentation of Blood Cells Based on Supervised Learning
inferred← citeshttps://doi.org/10.2174/2666255813999200904113251openalex-snapshot
Pathological Analysis of Blood Cells Using Deep Learning Techniques
inferred← citeshttps://doi.org/10.22214/ijraset.2020.5153openalex-snapshot
White Blood Cells Cancer detection using Edge Detection Segmentation and Convolutional Neural Network
inferred← citeshttps://doi.org/10.22214/ijraset.2023.54994openalex-snapshot
Analysis of Blood Samples to Identify Leukemia Cells using a Support Vector Machine and K-Nearest Neighbor Algorithms
inferred← citeshttps://doi.org/10.31590/ejosat.892170openalex-snapshot
The Leukemia Healthy and Unhealthy Detection with Wavelet Transform Based On Co-Occurrence Matrix and Support Vector Machine
inferred← citeshttps://doi.org/10.3389/fonc.2023.1223353openalex-snapshot
A lightweight network based on dual-stream feature fusion and dual-domain attention for white blood cells segmentation
inferred← citeshttps://doi.org/10.3390/cancers16020348openalex-snapshot
The Cross-Scale Association between Pathomics and Radiomics Features in Immunotherapy-Treated NSCLC Patients: A Preliminary Study
inferred← citeshttps://doi.org/10.34133/2022/9869518openalex-snapshot
An Overview of Organs-on-Chips Based on Deep Learning
inferred← citeshttps://doi.org/10.35940/ijitee.i1133.0789s19openalex-snapshot
Classifying White Blood Cells in Blood Smear Images using a Convolutional Neural Network
inferred← citeshttps://doi.org/10.58837/chula.the.2019.191openalex-snapshot
Automatic Method for Avian Red Blood Cell and Heterophil Counting Using Iterative Thresholding
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