Cheng et al., 2003 - Google Patents
Computer-aided detection and classification of microcalcifications in mammograms: a surveyCheng et al., 2003
View PDF- Document ID
- 10032358997304011997
- Author
- Cheng H
- Cai X
- Chen X
- Hu L
- Lou X
- Publication year
- Publication venue
- Pattern recognition
External Links
Snippet
Breast cancer continues to be a significant public health problem in the world. Approximately, 182,000 new cases of breast cancer are diagnosed and 46,000 women die of breast cancer each year in the United States. Even more disturbing is the fact that one out …
- 238000001514 detection method 0 title abstract description 116
Classifications
-
- 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
- G06T2207/30068—Mammography; Breast
-
- 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
- G06T2207/20048—Transform domain processing
- G06T2207/20064—Wavelet transform [DWT]
-
- 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
- G06T2207/10072—Tomographic images
- G06T2207/10088—Magnetic resonance imaging [MRI]
-
- 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
- G06K9/52—Extraction of features or characteristics of the image by deriving mathematical or geometrical properties from the whole image
- G06K9/527—Scale-space domain transformation, e.g. with wavelet analysis
-
- 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
- G06T2207/20156—Automatic seed setting
-
- 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
- G06T2207/10116—X-ray 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
- G06K9/62—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
- 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
-
- 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
- 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
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
- G06T5/007—Dynamic range modification
- G06T5/008—Local, e.g. shadow enhancement
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Cheng et al. | Computer-aided detection and classification of microcalcifications in mammograms: a survey | |
| Papadopoulos et al. | Improvement of microcalcification cluster detection in mammography utilizing image enhancement techniques | |
| Bozek et al. | A survey of image processing algorithms in digital mammography | |
| Ganesan et al. | Computer-aided breast cancer detection using mammograms: a review | |
| Dominguez et al. | Detection of masses in mammograms via statistically based enhancement, multilevel-thresholding segmentation, and region selection | |
| Bruce et al. | Classifying mammographic mass shapes using the wavelet transform modulus-maxima method | |
| Gupta et al. | A tool supported approach for brightness preserving contrast enhancement and mass segmentation of mammogram images using histogram modified grey relational analysis | |
| Jian et al. | Computer-aided diagnosis of breast microcalcifications based on dual-tree complex wavelet transform | |
| Seryasat et al. | Evaluation of a new ensemble learning framework for mass classification in mammograms | |
| Niranjana et al. | A review on image processing methods in detecting lung cancer using CT images | |
| Costaridou | Medical image analysis methods | |
| Singh et al. | An approach for classification of malignant and benign microcalcification clusters | |
| Sun et al. | Ipsilateral-mammogram computer-aided detection of breast cancer | |
| Pezeshki et al. | Mass classification of mammograms using fractal dimensions and statistical features | |
| Saranyaraj et al. | Region of Interest and Feature-based Analysis to Detect Breast Cancer from a Mammogram Image | |
| Ragab et al. | A comparison between support vector machine and artificial neural network for breast cancer detection | |
| Oprea et al. | A self organizing map approach to breast cancer detection | |
| Kekre et al. | Texture based segmentation using statistical properties for mammographic images | |
| EL NAQA et al. | Techniques in the detection of microcalcification clusters in digital mammograms | |
| Boujelben et al. | Automatic application level set approach in detection calcifications in mammographic image | |
| George et al. | Computer-Aided Detection of Breast Cancer on Mammograms: 169Extreme Learning Machine Neural Network Approach | |
| Pak et al. | Improvement of breast cancer detection using non-subsampled contourlet transform and super-resolution technique in mammographic images | |
| Sreedevi et al. | Fuzzy soft set approach for classifying malignant and benign breast tumours | |
| Vikramathithan et al. | Detection of Malignancy in Mammogram by CAD Tools–A Survey | |
| Richardson | Image enhancement of cancerous tissue in mammography images |