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Classification of mammogram images using the energy probability in frequency domain and most discriminative power coefficients

https://doi.org/10.1002/ima.22352
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/11578079_48openalex-snapshot
Diagnosis of Breast Cancer in Digital Mammograms Using Independent Component Analysis and Neural Networks
inferredcites →https://doi.org/10.1007/11816515_69openalex-snapshot
A Novel Computer-Aided Diagnosis System of the Mammograms
inferredcites →https://doi.org/10.1007/978-3-319-33793-7_2openalex-snapshot
An Overview of Pectoral Muscle Extraction Algorithms Applied to Digital Mammograms
inferredcites →https://doi.org/10.1007/978-981-10-1627-1_29openalex-snapshot
Automatic Detection of Suspicious Lesions in Digital X-ray Mammograms
inferredcites →https://doi.org/10.1007/s10916-010-9624-7openalex-snapshot
Classification of Benign and Malignant Breast Masses Based on Shape and Texture Features in Sonography Images
inferredcites →https://doi.org/10.1016/j.bbe.2017.09.003openalex-snapshot
Automated and effective content-based mammogram retrieval using wavelet based CS-LBP feature and self-organizing map
inferredcites →https://doi.org/10.1016/j.cmpb.2015.06.009openalex-snapshot
Breast cancer detection and classification in digital mammography based on Non-Subsampled Contourlet Transform (NSCT) and Super Resolution
inferredcites →https://doi.org/10.1016/j.neucom.2014.12.032openalex-snapshot
Mammogram classification using two dimensional discrete wavelet transform and gray-level co-occurrence matrix for detection of breast cancer
inferredcites →https://doi.org/10.1016/j.patcog.2009.11.001openalex-snapshot
Feature extraction using discrete cosine transform and discrimination power analysis with a face recognition technology
inferredcites →https://doi.org/10.1016/s0033-8389(05)70197-4openalex-snapshot
COMPUTER-AIDED DETECTION AND DIAGNOSIS OF BREAST CANCER
inferredcites →https://doi.org/10.1016/s1076-6332(99)80058-0openalex-snapshot
Improving breast cancer diagnosis with computer-aided diagnosis
inferredcites →https://doi.org/10.1080/00401706.1999.10485951openalex-snapshot
Statistical Learning Theory
inferredcites →https://doi.org/10.1080/23311916.2018.1444320openalex-snapshot
An approach for automatic lesion detection in mammograms
inferredcites →https://doi.org/10.1088/0031-9155/43/2/011openalex-snapshot
Automated classification of parenchymal patterns in mammograms
inferredcites →https://doi.org/10.1109/34.295913openalex-snapshot
Seeded region growing
inferredcites →https://doi.org/10.1109/anziis.2001.974051openalex-snapshot
Automatic pectoral muscle segmentation on mammograms by straight line estimation and cliff detection
inferredcites →https://doi.org/10.1109/iccsn.2010.95openalex-snapshot
Identifying Masses in Mammograms Using Template Matching
inferredcites →https://doi.org/10.1109/icedss.2017.8073694openalex-snapshot
Preprocessing filters for mammogram images: A review
inferredcites →https://doi.org/10.1109/icme.2006.262839openalex-snapshot
Face Recognition using Energy Probability in DCT Domain
inferredcites →https://doi.org/10.1109/iecbes.2010.5742205openalex-snapshot
Automated breast profile segmentation for ROI detection using digital mammograms
inferredcites →https://doi.org/10.1109/titb.2007.903514openalex-snapshot
A Novel Breast Tissue Density Classification Methodology
inferredcites →https://doi.org/10.1109/tmi.2001.974915openalex-snapshot
Guest editorial computer-aided diagnosis in medical imaging
inferredcites →https://doi.org/10.1109/wispnet.2016.7566558openalex-snapshot
Performance analysis and detection of micro calcification in digital mammograms using wavelet features
inferredcites →https://doi.org/10.1142/s021800149300073xopenalex-snapshot
IMAGE PROCESSING AND COMPUTER AIDED DIAGNOSIS IN DIGITAL MAMMOGRAPHY: A CLINICAL PERSPECTIVE
inferredcites →https://doi.org/10.1155/2013/104684openalex-snapshot
Hybrid Discrete Wavelet Transform and Gabor Filter Banks Processing for Features Extraction from Biomedical Images
inferredcites →https://doi.org/10.14716/ijtech.v7i1.1393openalex-snapshot
Classification of Digital Mammogram based on Nearest-Neighbor Method for Breast Cancer Detection
inferredcites →https://doi.org/10.17863/cam.105113openalex-snapshot
Mammographic Image Analysis Society (MIAS) database v1.21
inferredcites →https://doi.org/10.3233/his-170240openalex-snapshot
Content-based mammogram retrieval using wavelet based complete-LBP and K-means clustering for the diagnosis of breast cancer
inferredcites →https://doi.org/10.3233/thc-1993-1101openalex-snapshot
Technology and Health Care – Official Journal of the European Society for Engineering and Medicine: A New Journal
inferredcites →https://doi.org/10.5815/ijigsp.2014.04.07openalex-snapshot
Computer A ided Detection of Tumours in Mammograms

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/ima.22484openalex-snapshot
Detection and classification of breast cancer from digital mammograms using hybrid extreme learning machine classifier
inferred← citeshttps://doi.org/10.1002/ima.22512openalex-snapshot
Bone microarchitecture characterization based on fractal analysis in spatial frequency domain imaging
inferred← citeshttps://doi.org/10.1002/ima.22537openalex-snapshot
Early detection of breast malignancy using wavelet features and optimized classifier
inferred← citeshttps://doi.org/10.1002/ima.22589openalex-snapshot
Medical image denoising using optimal thresholding of wavelet coefficients with selection of the best decomposition level and mother wavelet
inferred← citeshttps://doi.org/10.1002/ima.22635openalex-snapshot
Malignancy detection on mammograms by integrating modified convolutional neural network classifier and texture features
inferred← citeshttps://doi.org/10.1007/s00432-023-04956-zopenalex-snapshot
Machine learning and deep learning techniques for breast cancer diagnosis and classification: a comprehensive review of medical imaging studies
inferred← citeshttps://doi.org/10.1007/s11042-022-12599-4openalex-snapshot
RETRACTED ARTICLE: Mammogram pectoral muscle removal and classification using histo-sigmoid based ROI clustering and SDNN
inferred← citeshttps://doi.org/10.1007/s11042-023-14708-3openalex-snapshot
Recognizing breast tumors based on mammograms combined with pre-trained neural networks
inferred← citeshttps://doi.org/10.1007/s12652-022-03713-3openalex-snapshot
Breast cancer detection in mammogram: combining modified CNN and texture feature based approach
inferred← citeshttps://doi.org/10.1007/s44174-025-00517-9openalex-snapshot
Enhanced 3D Breast Cancer Detection in Mammograms: Iterative Closest Point and Linde–Buzo–Gray Algorithm Fusion
inferred← citeshttps://doi.org/10.1016/j.aap.2021.106098openalex-snapshot
Speed violation analysis of heavy vehicles on highways using spatial analysis and machine learning algorithms
inferred← citeshttps://doi.org/10.1016/j.asoc.2026.115210openalex-snapshot
Two-level breast tumor classification with multi-view imaging and pathology-aware large language models: A fuzzy KNN and ensemble learning framework
inferred← citeshttps://doi.org/10.1016/j.cmpb.2021.106311openalex-snapshot
Spatial-Frequency dual-branch attention model for determining KRAS mutation status in colorectal cancer with T2-weighted MRI
inferred← citeshttps://doi.org/10.1016/j.imu.2020.100401openalex-snapshot
Classification of digital mammograms using information set features and Hanman Transform based classifiers
inferred← citeshttps://doi.org/10.1016/j.matpr.2020.10.858openalex-snapshot
WITHDRAWN: Correlation-based high distinction feature selection in digital mammogram
inferred← citeshttps://doi.org/10.1142/s0218126622501316openalex-snapshot
Selection of Optimal Thresholds in Multi-Level Thresholding Using Multi-Objective Emperor Penguin Optimization for Precise Segmentation of Mammogram Images
inferred← citeshttps://doi.org/10.1142/s0219519420500360openalex-snapshot
A NEW CAD SYSTEM FOR BREAST CANCER CLASSIFICATION USING DISCRIMINATION POWER ANALYSIS OF WAVELET’S COEFFICIENTS AND SUPPORT VECTOR MACHINE
inferred← citeshttps://doi.org/10.1515/bmt-2022-0006openalex-snapshot
Fetal phonocardiogram signals denoising using improved complete ensemble (EMD) with adaptive noise and optimal thresholding of wavelet coefficients
inferred← citeshttps://doi.org/10.21271/zjpas.34.2.3openalex-snapshot
Comprehensive Study for Breast Cancer Using Deep Learning and Traditional Machine Learning
inferred← citeshttps://doi.org/10.3390/pr9040682openalex-snapshot
Performance Evaluation of Epileptic Seizure Prediction Using Time, Frequency, and Time–Frequency Domain Measures
inferred← citeshttps://doi.org/10.53508/ijiam.1407152openalex-snapshot
Breast Cancer Image Classification using Convolutional Neural Networks (CNN) Models
inferred← citeshttps://doi.org/10.5772/intechopen.94026openalex-snapshot
Medical Image Classification Using the Discriminant Power Analysis (DPA) of Discrete Cosine Transform (DCT) Coefficients
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