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

Ljosa et al., 2009 - Google Patents

Introduction to the quantitative analysis of two-dimensional fluorescence microscopy images for cell-based screening

Ljosa et al., 2009

View HTML
Document ID
6127625065850208200
Author
Ljosa V
Carpenter A
Publication year
Publication venue
PLoS computational biology

External Links

Snippet

Modern automated microscopes collect digital images at an astonishing pace. Automated image analysis can measure biological phenotypes quantitatively and reliably, and has therefore become a powerful tool for probing a wide variety of biological questions using …
Continue reading at journals.plos.org (HTML) (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
    • G06T2207/30024—Cell structures in vitro; Tissue sections in vitro
    • 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
    • G06T2207/20—Special algorithmic details
    • G06T2207/20092—Interactive image processing based on input by user
    • G06T2207/20104—Interactive definition of region of interest [ROI]
    • 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
    • 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
    • G06T2207/10—Image acquisition modality
    • G06T2207/10056—Microscopic 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
    • G06K9/00127—Acquiring and recognising microscopic objects, e.g. biological cells and cellular parts
    • G06K9/0014—Pre-processing, e.g. image segmentation ; Feature extraction
    • 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
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/20—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for hybridisation or gene expression, e.g. microarrays, sequencing by hybridisation, normalisation, profiling, noise correction models, expression ratio estimation, probe design or probe optimisation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00—Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/10—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology
    • G06F19/28—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for programming tools or database systems, e.g. ontologies, heterogeneous data integration, data warehousing or computing architectures
    • 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
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions

Similar Documents

Publication Publication Date Title
Ljosa et al. Introduction to the quantitative analysis of two-dimensional fluorescence microscopy images for cell-based screening
Jeckel et al. Advances and opportunities in image analysis of bacterial cells and communities
Lu et al. Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting
Caicedo et al. Data-analysis strategies for image-based cell profiling
Cutler et al. Omnipose: a high-precision morphology-independent solution for bacterial cell segmentation
Phillip et al. A robust unsupervised machine-learning method to quantify the morphological heterogeneity of cells and nuclei
Molnar et al. Accurate morphology preserving segmentation of overlapping cells based on active contours
Arena et al. Quantitating the cell: turning images into numbers with ImageJ
Sommer et al. Machine learning in cell biology–teaching computers to recognize phenotypes
Rittscher Characterization of biological processes through automated image analysis
Kothari et al. Pathology imaging informatics for quantitative analysis of whole-slide images
Pennekamp et al. Implementing image analysis in laboratory‐based experimental systems for ecology and evolution: a hands‐on guide
Fuchs et al. Computational pathology: challenges and promises for tissue analysis
Shariff et al. Automated image analysis for high-content screening and analysis
JP2022527145A (en) Multiple instance Lana for predictive organizational pattern identification
Dzyubachyk et al. Automated analysis of time-lapse fluorescence microscopy images: from live cell images to intracellular foci
Balomenos et al. Image analysis driven single-cell analytics for systems microbiology
Li et al. Chapter 17: bioimage informatics for systems pharmacology
Handfield et al. Unsupervised clustering of subcellular protein expression patterns in high-throughput microscopy images reveals protein complexes and functional relationships between proteins
Sbalzarini Seeing is believing: quantifying is convincing: computational image analysis in biology
Mace et al. Extraction and comparison of gene expression patterns from 2D RNA in situ hybridization images
Marée The need for careful data collection for pattern recognition in digital pathology
Puniyani et al. SPEX2: automated concise extraction of spatial gene expression patterns from Fly embryo ISH images
Zinchuk et al. Machine learning for analysis of microscopy images: a practical guide
Baatz et al. Automated analysis and detailed quantification of biomedical images using definiens cognition network technology®