Huang et al., 2008 - Google Patents
Adaptive automatic segmentation of HEp-2 cells in indirect immunofluorescence imagesHuang et al., 2008
- Document ID
- 14669656222252173856
- Author
- Huang Y
- Jao Y
- Hsieh T
- Chung C
- Publication year
- Publication venue
- 2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008)
External Links
Snippet
Indirect immunofluorescence (IIF) with HEp-2 cells is used for the detection of antinuclear autoantibodies (ANA) in systemic autoimmune diseases. An automatic inspection system for ANA testing can be divided into HEp-2 cell detection, fluorescence pattern classification and …
- 230000011218 segmentation 0 title abstract description 23
Classifications
-
- 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
- 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
- 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
- G06T2207/30—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
- 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
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
-
- 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
- G06K9/00442—Document analysis and understanding; Document recognition
-
- 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
- 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
- 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
-
- 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
- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30244—Information retrieval; Database structures therefor; File system structures therefor in image databases
- G06F17/30247—Information retrieval; Database structures therefor; File system structures therefor in image databases based on features automatically derived from the image data
-
- 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 |
---|---|---|
Huang et al. | Adaptive automatic segmentation of HEp-2 cells in indirect immunofluorescence images | |
Li et al. | Segmentation of white blood cell from acute lymphoblastic leukemia images using dual‐threshold method | |
Zhang et al. | Segmentation of cytoplasm and nuclei of abnormal cells in cervical cytology using global and local graph cuts | |
Zhang et al. | Automation‐assisted cervical cancer screening in manual liquid‐based cytology with hematoxylin and eosin staining | |
Tonti et al. | An automated approach to the segmentation of HEp-2 cells for the indirect immunofluorescence ANA test | |
JP2003506796A (en) | Method and apparatus for providing a color threshold in use of an optical microscope | |
Percannella et al. | A classification-based approach to segment HEp-2 cells | |
Huang et al. | Outline detection for the HEp-2 cell in indirect immunofluorescence images using watershed segmentation | |
CN110335233A (en) | Defect detection system and method for expressway guardrail board based on image processing technology | |
Halim et al. | Nucleus detection on pap smear images for cervical cancer diagnosis: A review analysis | |
Hsieh et al. | HEp-2 cell classification in indirect immunofluorescence images | |
Savkare et al. | Automatic blood cell segmentation using K-Mean clustering from microscopic thin blood images | |
GB2329014A (en) | Automated identification of tubercle bacilli | |
Lezoray et al. | Segmentation of cytological image using color and mathematical morphology | |
EP1565873B1 (en) | Particle extraction for automatic flow microscope | |
Huang et al. | HEp-2 cell images classification based on textural and statistic features using self-organizing map | |
Shaikh et al. | Image binarization using iterative partitioning: A global thresholding approach | |
CN109741351A (en) | A class-sensitive edge detection method based on deep learning | |
Valizadeh et al. | A novel hybrid algorithm for binarization of badly illuminated document images | |
CN113989588A (en) | Self-learning-based intelligent evaluation system and method for pentagonal drawing test | |
Nugroho et al. | Automated detection of plasmodium ovale and malariae species on microscopic thin blood smear images | |
Zhang et al. | Extraction of karyocytes and their components from microscopic bone marrow images based on regional color features | |
Sertel et al. | Computer-aided prognosis of neuroblastoma: classification of stromal development on whole-slide images | |
Abdullah et al. | An accurate thresholding-based segmentation technique for natural images | |
RU2571510C2 (en) | Method and apparatus using image magnification to suppress visible defects on image |