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

Şekeroğlu et al., 2018 - Google Patents

A computer aided diagnosis system for lung cancer detection using support vector machine

Şekeroğlu et al., 2018

Document ID
6698014372873578074
Author
Şekeroğlu B
Emirzade E
Publication year
Publication venue
Third international workshop on pattern recognition

External Links

Snippet

Computer aided diagnosis (CAD) is started to be implemented broadly in the diagnosis and detection of many varieties of abnormalities acquired during various imaging procedures. The main aim of the CAD systems is to increase the accuracy and decrease the time of …
Continue reading at www.spiedigitallibrary.org (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/30Subject of image; Context of image processing
    • G06T2207/30004Biomedical image processing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/0002Inspection of images, e.g. flaw detection
    • G06T7/0012Biomedical image inspection
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20112Image segmentation details
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10072Tomographic images
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/36Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46Extraction of features or characteristics of the image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30244Information retrieval; Database structures therefor; File system structures therefor in image databases
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10116X-ray image
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/32Medical data management, e.g. systems or protocols for archival or communication of medical images, computerised patient records or computerised general medical references
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
    • G06T3/0031Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image for topological mapping of a higher dimensional structure on a lower dimensional surface
    • G06T3/0037Reshaping or unfolding a 3D tree structure onto a 2D plane
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K2209/00Indexing scheme relating to methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/002D [Two Dimensional] image generation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image

Similar Documents

Publication Publication Date Title
Yan et al. DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning
Dalmış et al. Fully automated detection of breast cancer in screening MRI using convolutional neural networks
Sumathipala et al. Prostate cancer detection from multi-institution multiparametric MRIs using deep convolutional neural networks
Hancock et al. Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the Lung Image Database Consortium dataset with two statistical learning methods
Tsehay et al. Convolutional neural network based deep-learning architecture for prostate cancer detection on multiparametric magnetic resonance images
Firmino et al. Computer-aided detection system for lung cancer in computed tomography scans: review and future prospects
Shaukat et al. Computer-aided detection of lung nodules: a review
Park et al. Colonoscopic polyp detection using convolutional neural networks
Echegaray et al. Core samples for radiomics features that are insensitive to tumor segmentation: method and pilot study using CT images of hepatocellular carcinoma
Vijila Rani et al. Lung lesion classification scheme using optimization techniques and hybrid (KNN-SVM) classifier
Bergtholdt et al. Pulmonary nodule detection using a cascaded SVM classifier
Orooji et al. Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography
Liu et al. Mediastinal lymph node detection on thoracic CT scans using spatial prior from multi-atlas label fusion
Ma et al. Combining population and patient-specific characteristics for prostate segmentation on 3D CT images
Goel et al. Improved detection of kidney stone in ultrasound images using segmentation techniques
Zhao et al. A deep-learning based automatic pulmonary nodule detection system
Pérez et al. Automated detection of lung nodules with three-dimensional convolutional neural networks
Blumenfeld et al. Pneumothorax detection in chest radiographs using convolutional neural networks
Şekeroğlu et al. A computer aided diagnosis system for lung cancer detection using support vector machine
Rampun et al. Classification of mammographic microcalcification clusters with machine learning confidence levels
Hogeweg et al. Foreign object detection and removal to improve automated analysis of chest radiographs
Hamidinekoo et al. Comparing the performance of various deep networks for binary classification of breast tumours
George et al. Mammogram breast density classification using mean-elliptical local binary patterns
Leite et al. 3D texture-based classification applied on brain white matter lesions on MR images
Samala et al. Homogenization of breast MRI across imaging centers and feature analysis using unsupervised deep embedding