Abstract
This work consists of the development of a computer scheme to provide the processing of digital mammographic images sent by an Internet user. The current system results provide indications on the suspicious mammogram regions with the detected lesions. Besides the image with convenient marks on detected clustered microcalcifications, their classification in terms of “suspect” or “nonsuspect” is also provided. The density level, as well as the percentage probabilities regarding the BIRADS® classification and the mass margin shapes are presented for suspicious masses detected by the scheme. The user can upload regions of interest (ROIs). For digitized mammograms, the correct rate of was 93% for microcalcification detection, while for mass detection, it was 92%. For direct digital mammograms, the correct rate was 93% for microcalcification detection, while for mass detection, it was 89%. In addiction, it was verified that the processing time average varied between 10s (the best case: one ROI) and 1,5 minutes (the worst case: four mammograms), which this time can be considered acceptable. According to the tests performed with the purpose of checking the system efficacy, the tools manipulation was qualified as easy by 72% of the volunteers whom have tested the system and its working classified as great (40%) and good (56%). Currently, there are CAD schemes available on the market, however, they present a high acquisition cost and a final answer restricted just to the detection of suspect lesions, without providing additional data that can enhance the information the radiologists have, therefore helping them on their report. This research was carried out in order to provide this additional data by the Internet. Even though some problems occurred with the transmission of images by the Internet, the results presented by the tests performed by volunteers showed that the system has a good performance; it’s available at: http://lapimo.sel.eesc.usp.br/lapimo/lapimo.htm.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Referencias
Goes C.E. (2002) Segmentação de Imagens Mamográficas Digitais para Detecção de Microcalcificações dm Mamas Densas. Dissertação de Mestrado — Depto. de Eng. Elétrica, EESC/USP, São Carlos, p.124
Cheng, H.D.; Cai, X.; Chen, X.; Hu, L.; Lou, X. (2003). Computeraided detection and classification of microcalcification in mammograms: a survey. Pattern Recognition, v. 36, p. 2937–2991.
Kallergi, M. (2004). “Computer-aided diagnosis of mammographic microcalcification clusters” Medical Physics, v. 31, n. 2, p. 314–326
Santos, V.T. (2002), Segmentação de imagens mamográficas para detecção de nódulos em mamas densas, Dissertação de Mestrado — Depto. de Eng. Elétrica, EESC/USP, São Carlos, p. 112.
Hadjiiski, L.; Chan, H-P.; Sahiner, B.; et al. (2004). Improvement in radiologists’ characterization of malignant and benign breast masses on serial mammograms with computer-aided diagnosis: an ROC study. Radiology, v. 233, p. 255–265
Ji, T. L.; Sundareshan, M. K.; Roehrig, H. (1994). Adaptive image contrast enhancement based on human visual properties. IEEE Transactions on Medical Imaging, v. 13, p. 573–584
Nunes, F.L.S.; Schiabel, H.; Benatti, R.H. (2002). Contrast enhancement in dense breast images using the modulation transfer function. Medical Physics, v. 29, n. 12, p. 2925–2936
Maceratini, R.; Sabbatini, R. M. E. (1994) Telemedicina: A Nova Revolução. Revista Informédica, v. 1, n. 6, p. 5–9
Vieira, M.A.C. (2005) Metodologia baseada nas Funções de Transferência para Pré-Processamento de Imagens Mamográficas Digitais e sua Aplicação em Esquema Computacional de Auxílio ao Diagnóstico, Tese de Doutorado — Depto. de Eng. Elétrica, EESC/USP, São Carlos, p. 203.
Patrocinio, A. C. (2004). Classificador automático de achados mamográficos em imagens digitais de mamas densas utilizando técnicas híbridas. Tese de Doutorado — Depto. de Eng. Elétrica, EESC/USP, São Carlos, p. 191.
Ribeiro, P.B.; Schiabel, H.; Patrocinio, A.C. (2006) Improvement in ANN Performance by the Selection of the Best Texture Festures from Breast Masses in Mammography Images. In: World Congress on Medical Physics and Biomedical Engineering 2006, Seoul, Korea.
Li, H et al. (2006) Comparasion of Computerized Image Analyses for Digitized Screen-Film Mammograms and Full-Field Digital Mammography Images. IWDM 2006, p. 569–575.
Baum, F.; Fischer, U.; Obenauer, S.; Grabbe, E. (2002) Computeraided detection in direct digital full-field mammography: initial results. European Radiology, v. 12, n.12, p. 3015–3017.
Obenauer, S.; Sohns, C.; Werner, C.; Grabbe, E. (2006) Impact of Breast Density on Computer-Aided Detection in Full-Field Digital Mammography. Journal of Digital Imaging, v.0, p.1–7.
Nishikawa, R.M. et al. (1992) Computer-aided detection of clustered microcalcifications. In: IEEE International Conference on Systems, Man and Cybernetics. Chicago. Proceedings, p.1375–1378.
Wallet, B. C.; Solka, J. L.; Priebe, C. E. (1997). A Method for Detecting Microcalcifications in Digital Mammograms. Journal of Digital Imaging, v. 10, p. 136–139.
Escarpinati, M. C.; Vieira, M. A. C.; Schiabel, H. (2002) Computer Technique for Digital Radiographic Images Correction Based On The Characteristic Curve. Journal of Digital Imaging, v. 15,Suppl. 1, p. 228–230.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Angelo, M.F., Schiabel, H., Patrocinio, A.C., Freitas, L.P. (2007). CAD.net: uma Ferramenta de Processamento de Imagens Mamográficas e Auxílio ao Diagnóstico via-Internet. In: Müller-Karger, C., Wong, S., La Cruz, A. (eds) IV Latin American Congress on Biomedical Engineering 2007, Bioengineering Solutions for Latin America Health. IFMBE Proceedings, vol 18. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74471-9_210
Download citation
DOI: https://doi.org/10.1007/978-3-540-74471-9_210
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74470-2
Online ISBN: 978-3-540-74471-9
eBook Packages: EngineeringEngineering (R0)