Nothing Special   »   [go: up one dir, main page]

Vromen et al., 2009 - Google Patents

Red blood cell segmentation from SEM images

Vromen et al., 2009

View PDF
Document ID
3827892046235605782
Author
Vromen J
McCane B
Publication year
Publication venue
2009 24th International Conference Image and Vision Computing New Zealand

External Links

Snippet

We present a model based contour tracing approach to the problem of automatically segmenting a scanning electron microscope image of red blood cells. We use a second order polynomial model and a simple Bayesian approach to ensure smooth boundaries, and …
Continue reading at reflect.otago.ac.nz (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Electro-optical investigation, e.g. flow cytometers
    • G01N15/1456—Electro-optical investigation, e.g. flow cytometers without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals
    • G01N15/1459—Electro-optical investigation, e.g. flow cytometers without spatial resolution of the texture or inner structure of the particle, e.g. processing of pulse signals the analysis being performed on a sample stream
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20212—Image combination
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume, or surface-area of porous materials
    • G01N15/10—Investigating individual particles
    • G01N15/14—Electro-optical investigation, e.g. flow cytometers
    • G01N15/1468—Electro-optical investigation, e.g. flow cytometers with spatial resolution of the texture or inner structure of the particle
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/20—Image acquisition
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

Similar Documents

Publication Publication Date Title
Chadha et al. An automated method for counting red blood cells using image processing
Putzu et al. Leucocyte classification for leukaemia detection using image processing techniques
US8135202B2 (en) Automated method and system for nuclear analysis of biopsy images
US20130094750A1 (en) Methods and systems for segmentation of cells for an automated differential counting system
Hortinela et al. Identification of abnormal red blood cells and diagnosing specific types of anemia using image processing and support vector machine
Reta et al. Segmentation of bone marrow cell images for morphological classification of acute leukemia
US20060204953A1 (en) Method and apparatus for automated analysis of biological specimen
Vromen et al. Red blood cell segmentation from SEM images
CN110120056A (en) Blood leucocyte dividing method based on self-adapting histogram threshold value and contour detecting
Bhavnani et al. Segmentation and counting of WBCs and RBCs from microscopic blood sample images
Jagadeesh et al. Image processing based approach to cancer cell prediction in blood samples
Sajjad et al. Computer aided system for leukocytes classification and segmentation in blood smear images
Benomar et al. Multi-feature-based approach for white blood cells segmentation and classification in peripheral blood and bone marrow images
Tomari et al. Red blood cell counting analysis by considering an overlapping constraint
US8538122B2 (en) Localization of a valid area of a blood smear
Evangeline et al. Computer aided system for human blood cell identification, classification and counting
Elen et al. A new approach for fully automated segmentation of peripheral blood smears
Aazad et al. Deciphering Blood Cells-Method for Blood Cell Analysis using Microscopic Images
Shirazi et al. Accurate microscopic red blood cell image enhancement and segmentation
CN110766680B (en) A method of leukocyte image segmentation based on geometric constraints
Rege et al. Automatic leukemia identification system using otsu image segmentation and mser approach for microscopic smear image database
Chaudhari et al. Microscope image processing: an overview
Danyali et al. Robust leukocyte segmentation in blood microscopic images based on intuitionistic fuzzy divergence
Li et al. Automatic detecting and recognition of casts in urine sediment images
WO2012061619A2 (en) System and method for improved detection of objects of interest in image data by management of false positives