An automatic method to discriminate malignant masses from normal tissue in digital mammograms

Physics in Medicine and Biology

Volumn 45, Issue 10, 2000, Pages 2843-2857

  Te Brake, G M ^a   Karssemeijer, N ^a   Hendriks, J H C L ^a  

^a RADBOUD UNIVERSITY MEDICAL CENTER   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER AIDED DIAGNOSIS; NEURAL NETWORKS; TISSUE;

MALIGNANT MASSES; TUMOR DISCRIMINATION;

MAMMOGRAPHY;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BENIGN TUMOR; BREAST CANCER; DIFFERENTIAL DIAGNOSIS; HUMAN; IMAGE ANALYSIS; MALIGNANT NEOPLASTIC DISEASE; MAMMOGRAPHY; PRIORITY JOURNAL;

BREAST NEOPLASMS; FALSE POSITIVE REACTIONS; FEMALE; HUMAN; IMAGE PROCESSING, COMPUTER-ASSISTED; MAMMOGRAPHY; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); SENSITIVITY AND SPECIFICITY; SUPPORT, NON-U.S. GOV'T; TIME FACTORS;

EID: 0033772931     PISSN: 00319155     EISSN: None     Source Type: Journal    
DOI: 10.1088/0031-9155/45/10/308     Document Type: Article

References (22)

1. Analysis of cancers missed at screening mammography
2. Single and multi-scale detection of masses in digital mammograms
3. Screening interval breast cancers: Mammographic features and prognostic factors
4. Automated classification of parenchymal patterns in mammograms
5. Detection of stellate distortions in mammograms
6. Computer-aided mammographic screening for spiculated lesions
7. A discrete dynamic contour model
8. Deformable models in medical image analysis: A survey
9. Computer-aided breast cancer detection and diagnosis of masses using difference of gaussians and derivative-based feature saliency
10. Classification of mass and normal breast tissue: A convolution neural network classifier with spatial domain and texture images
11. Automated detection of breast carcinomas not detected in a screening program
12. A discrete dynamic contour model for mass segmentation in digital mammograms
13. Invasive interval cancers in the Ostergotland mammographic screening programme: Radiological analysis
14. Classification of mass and normal breast tissue on digital mammograms: Multiresolution texture analysis
15. Comparison of bilateral-substraction and single-image processing techniques in the computerized detection of mammographic masses