[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Montironi et al., 1995 - Google Patents

Prostatic intraepithelial neoplasia: quantitation of the basal cell layer with machine vision system

Montironi et al., 1995

Document ID
6226771399805993962
Author
Montironi R
Bartels P
Thompson D
Bartels H
Scarpelli M
Publication year
Publication venue
Pathology-Research and Practice

External Links

Snippet

The aim of this paper is to report on a fully automated procedure to quantify the epithelial cell components in prostatic intraepithelial neoplasia with particular emphasis on the basal cell layer (BCL). Scene segmentation was guided by a knowledgebased system of digitized …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay
    • G01N33/574—Immunoassay; Biospecific binding assay for cancer
    • G01N33/57407—Specifically defined cancers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
    • G01N33/48—Investigating or analysing materials by specific methods not covered by the preceding groups biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/5005—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving human or animal cells
    • 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
    • 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
    • G06K9/00147—Matching; Classification
    • 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
    • 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

Similar Documents

Publication Publication Date Title
Khameneh et al. Automated segmentation of cell membranes to evaluate HER2 status in whole slide images using a modified deep learning network
Loukas et al. An image analysis‐based approach for automated counting of cancer cell nuclei in tissue sections
Di Cataldo et al. Computer-aided techniques for chromogenic immunohistochemistry: status and directions
Keenan et al. An automated machine vision system for the histological grading of cervical intraepithelial neoplasia (CIN)
Payne et al. Sputum screening by quantitative microscopy a reexamination of a portion of the National Cancer Institute cooperative early lung cancer study
US20060067887A1 (en) Scoring estrogen and progesterone receptors expression based on image analysis
US20080166035A1 (en) Computer-Aided Pathological Diagnosis System
US11631171B2 (en) Automated detection and annotation of prostate cancer on histopathology slides
US20070135999A1 (en) Method, apparatus and system for characterizing pathological specimen
Tambasco et al. Quantifying the architectural complexity of microscopic images of histology specimens
Hofstädter et al. Cell proliferation assessment in oncology
Bacus et al. Image morphometric nuclear grading of intraepithelial neoplastic lesions with applications to cancer chemoprevention trials
Priego-Torres et al. Deep learning-based instance segmentation for the precise automated quantification of digital breast cancer immunohistochemistry images
Papke Jr et al. Computational augmentation of neoplastic endometrial glands in digital pathology displays
Lu et al. Immunohistochemical quantification of expression of a tight junction protein, claudin-7, in human lung cancer samples using digital image analysis method
Swiderska-Chadaj et al. Content-based analysis of Ki-67 stained meningioma specimens for automatic hot-spot selection
Li et al. Skin cells segmentation algorithm based on spectral angle and distance score
Charpin et al. Correlation of nucleolar organizer regions and nuclear morphometry assessed by automatic image analysis in breast cancer with aneuploidy, K167 immunostaining, histopathologic grade and lymph node involvement
Feng et al. An advanced automated image analysis model for scoring of ER, PR, HER-2 and Ki-67 in breast carcinoma
Montironi et al. Prostatic intraepithelial neoplasia: quantitation of the basal cell layer with machine vision system
Gao et al. Differential diagnosis of lung carcinoma with three-dimensional quantitative molecular vibrational imaging
Vidal et al. A fully automated approach to prostate biopsy segmentation based on level-set and mean filtering
Korzynska et al. The METINUS Plus method for nuclei quantification in tissue microarrays of breast cancer and axillary node tissue section
Neuman et al. Segmentation of stained lymphoma tissue section images
Ortiz De Solorzano et al. Applications of quantitative digital image analysis to breast cancer research