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Titolo:
Digital mammography: Wavelet transform and Kalman-filtering neural networkin mass segmentation and detection
Autore:
Qian, W; Sun, XJ; Song, DS; Clark, RA;
Indirizzi:
Univ S Florida, Coll Med, H Lee Moffitt Canc Ctr & Res Inst, Dept Interdisciplinary Oncol, Tampa, FL 33612 USA Univ S Florida Tampa FL USA 33612 disciplinary Oncol, Tampa, FL 33612 USA Univ S Florida, Coll Med, H Lee Moffitt Canc Ctr & Res Inst, Dept Radiol, Tampa, FL 33612 USA Univ S Florida Tampa FL USA 33612 Inst, Dept Radiol, Tampa, FL 33612 USA
Titolo Testata:
ACADEMIC RADIOLOGY
fascicolo: 11, volume: 8, anno: 2001,
pagine: 1074 - 1082
SICI:
1076-6332(200111)8:11<1074:DMWTAK>2.0.ZU;2-P
Fonte:
ISI
Lingua:
ENG
Soggetto:
COMPUTER-ASSISTED DIAGNOSIS; AUTOMATED DETECTION; 2 VIEWS; CLASSIFICATION; BREAST; MICROCALCIFICATIONS;
Keywords:
breast neoplasms; diagnosis; breast radiography; computers; diagnostic aid;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Citazioni:
28
Recensione:
Indirizzi per estratti:
Indirizzo: Qian, W Univ S Florida, Coll Med, H Lee Moffitt Canc Ctr & Res Inst, Dept Interdisciplinary Oncol, 12902 Magnolia Dr, Tampa, FL 33612 USA Univ S Florida 12902 Magnolia Dr Tampa FL USA 33612 , FL 33612 USA
Citazione:
W. Qian et al., "Digital mammography: Wavelet transform and Kalman-filtering neural networkin mass segmentation and detection", ACAD RADIOL, 8(11), 2001, pp. 1074-1082

Abstract

Rationale and Objectives. The authors developed a new adaptive module to improve their computer-assisted diagnostic (CAD) method for mass segmentation and classification. The goal was an adaptive module that used a novel four-channel wavelet transform with neural network rather than a two-channel wavelet transform with manual subimage selection. The four-channel wavelet transform is used for image decomposition and reconstruction. and a novel Kalman-filtering neural network is used for adaptive subimage selection. Materials and Methods. The adaptive CAD module was compared with the nonadaptive module by comparing receiver operating characteristic curves for thewhole CAD system. An image database containing 800 regions of interest enclosing all mass types and normal tissues was used for the relative comparison of system performance, with electronic ground truth established in advance. Results. The receiver operating characteristic curves yield Az values of 0.93 and 0.86 with and without the adaptive module respectively. suggesting that overall CAD performance is improved with the adaptive module. Conclusion. The results of this study confirm the importance of using a new class of adaptive CAD methods that allow a more generalized application for larger image databases or images generated from different sensors or by means of direct x-ray detection. as required for clinical trials.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 20/09/20 alle ore 07:29:30