[go: up one dir, main page]

Zhu et al., 2017 - Google Patents

A partially supervised Bayesian image classification model with applications in diagnosis of sentinel lymph node metastases in breast cancer

Zhu et al., 2017

View PDF
Document ID
11398152335618052361
Author
Zhu Y
Fearn T
Chicken D
Austwick M
Somasundaram S
Mosse C
Clark B
Bigio I
Keshtgar M
Bown S
Publication year
Publication venue
arXiv preprint arXiv:1712.09853

External Links

Snippet

A method has been developed for the analysis of images of sentinel lymph nodes generated by a spectral scanning device. The aim is to classify the nodes, excised during surgery for breast cancer, as normal or metastatic. The data from one node constitute spectra at 86 …
Continue reading at arxiv.org (PDF) (other versions)

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
    • G06K9/62—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
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • 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
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • 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
    • G06K9/6279—Classification techniques relating to the number of classes
    • 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
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • 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
    • G06K2209/00—Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K2209/05—Recognition of patterns in medical or anatomical images
    • 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
    • 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
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass

Similar Documents

Publication Publication Date Title
Distante et al. Handbook of image processing and computer vision
EP3907658B1 (en) Hyperspectral demixing using foveated compressive projections
US10192099B2 (en) Systems and methods for automated screening and prognosis of cancer from whole-slide biopsy images
US8639043B2 (en) Classifying image features
US10055551B2 (en) Systems and methods for quantitative analysis of histopathology images using multiclassifier ensemble schemes
Sajda et al. Recovery of constituent spectra using non-negative matrix factorization
Song et al. Hybrid deep autoencoder with curvature gaussian for detection of various types of cells in bone marrow trephine biopsy images
Chavez et al. Breast cancer detection with low-dimensional ordered orthogonal projection in terahertz imaging
Gutierrez-Navarro et al. Blind end-member and abundance extraction for multispectral fluorescence lifetime imaging microscopy data
Qin et al. Target/background classification regularized nonnegative matrix factorization for fluorescence unmixing
Zhu et al. A partially supervised Bayesian image classification model with applications in diagnosis of sentinel lymph node metastases in breast cancer
Pant et al. Hyperspectral Anomaly Detection Methods: A Survey and Comparative Study
Olson et al. A study of anomaly detection performance as a function of relative spectral abundances for graph-and statistics-based detection algorithms
Ientilucci Hyperspectral sub-pixel target detection using hybrid algorithms and Physics Based Modeling
Chavez Esparza Statistical Machine Learning for Breast Cancer Detection with Terahertz Imaging
Esparza Statistical Machine Learning for Breast Cancer Detection with Terahertz Imaging
Majee et al. A model based neuron detection approach using sparse location priors
Di Leo et al. A web-based application for dermoscopic measurements and learning
Clausi Improved texture recognition of SAR sea ice imagery by data fusion of MRF features with traditional methods
Maurya et al. Hicf: a matlab package for hyperspectral image classification and fusion for educational learning and research
Liu et al. A foreground/background separation framework for interpreting polarimetric SAR images
Echriti Unsupervised wood and leaf classification from LiDAR point clouds utilising adaptive radius search and Gaussian Mixture Models
Lopez Unmixing in Very High Spatial Resolution Hyperspectral Images
Messer On the development of robust anomaly detection algorithms with limited labeled data
Ploeg et al. Improving Pathological Distribution Measurements with Bayesian Uncertainty