Breast cancer detection and classification in digital mammography based on Non-Subsampled Contourlet Transform (NSCT) and Super Resolution

Computer Methods and Programs in Biomedicine

Volumn 122, Issue 2, 2015, Pages 89-107

  Pak, Fatemeh ^a   Kanan, Hamidreza Rashidy ^a   Alikhassi, Afsaneh ^b  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b TEHRAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

Author keywords

BI RADS; Breast cancer; Computer Aided Diagnosis (CAD) system; Mammography; Non Subsampled Contourlet Transform (NSCT); Super Resolution (SR)

Indexed keywords

ADAPTIVE BOOSTING; ALGORITHMS; COMPUTER AIDED DIAGNOSIS; DIAGNOSIS; DISEASES; EXTRACTION; FEATURE EXTRACTION; IMAGE ENHANCEMENT; IMAGE SEGMENTATION; MAMMOGRAPHY; OPTICAL RESOLVING POWER;

BI-RADS; BREAST CANCER; COMPUTER AIDED DIAGNOSIS(CAD); NON SUBSAMPLED CONTOURLET TRANSFORM (NSCT); SUPER RESOLUTION;

IMAGE PROCESSING;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BREAST CANCER; CANCER CLASSIFICATION; CANCER DIAGNOSIS; CLINICAL FEATURE; DIGITAL MAMMOGRAPHY; FRACTAL ANALYSIS; HUMAN; INTERMETHOD COMPARISON; LEARNING ALGORITHM; NON SUBSAMPLED CONTOURLET TRANSFORM; SUPPORT VECTOR MACHINE; ALGORITHM; AUTOMATED PATTERN RECOGNITION; BREAST TUMOR; FEMALE; FUZZY LOGIC; IMAGE ENHANCEMENT; MACHINE LEARNING; MAMMOGRAPHY; PROCEDURES; RADIOGRAPHY; REPRODUCIBILITY; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING;

ALGORITHMS; BREAST NEOPLASMS; FEMALE; FUZZY LOGIC; HUMANS; MACHINE LEARNING; MAMMOGRAPHY; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; REPRODUCIBILITY OF RESULTS; SAMPLE SIZE; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84944277396     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2015.06.009     Document Type: Article

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