Computer-aided thyroid nodule detection in ultrasound images

Proceedings - IEEE Symposium on Computer-Based Medical Systems

Volumn , Issue , 2005, Pages 271-276

  Maroulis, D E ^a   Savelonas, M A ^a   Karkanis, S A ^b   Iakovidis, D K ^a   Dimitropoulos, N ^c  

^a UNIVERSITY OF ATHENS   (Greece)

^b TECHNOLOGICAL EDUCATIONAL INSTITUTE OF LAMIA   (Greece)

^c Euromedica Medical Center   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

DISEASES; IMAGE SEGMENTATION; PATIENT MONITORING; TUMORS; ULTRASONIC IMAGING;

HYPERFUNCTIONS; THYROID CANCER; ULTRASOUND (US) IMAGES;

COMPUTER AIDED DIAGNOSIS;

EID: 27544456800     PISSN: 10637125     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. S. Feld et all, "AACE Clinical Practice Guidelines for the Diagnosis and Management of Thyroid Nodules", Endocrine Practice, Jan./Feb. 1996, pp. 78-84.
2. W. Kass, A. Witkin, D. Terzopoulos, "Snakes: Active Contour Models", Int. J. Comput. Vision, vol. 1, no. 4, 1987, pp. 321-331.
3. T.F. Chan, L.A. Vesse, "Active Contours Without Edges", IEEE Trans. Image Processing, Feb. 2001, pp. 266-277.
4. T. McInerney, D. Terzopoulos, "Topologically Adaptable Snakes", Proc. Int. Conf. Comp. Vis., Cambridge, Jun. 1995, pp. 840-845.
5. C.M. Chen, H.H.S Lu, A.T. Hsiao, "A Dual-Snake Model of High Penetrability for Ultrasound Image Boundary Extraction", Ultrasound in Med. & Biol., vol.27, no.12, 2001, pp. 1651-1665.
6. M.E. Plissiti, D.I. Fotiadis, L.K. Michails, G.E. Bozios, "An Automated Method for Lumen and Media-Adventitia Border Detection in a Sequence of IVUS Frames", IEEE Trans. On Inf. Tec. in Biomedicine, vol. 8, no. 2, Jun. 2004, pp. 131-141.
7. R.F. Chang, W.J. Wu, C.C. Tseng, D.R. Chen, W.K. Moon, "3-D Snake for US in Margin Evaluation for Malignant Breast Tumor Excision Using Mammotome", IEEE Trans. On Inf. Tec. in Biomedicine, vol. 7, no. 3, Sep. 2003.
8. E. Angelini, J. Holmes, A. Laine, "Segmentation of RT3D Ultrasound with Implicit Deformable Models Without Gradients", Proc. ISPA 2003, Rome, Italy, Sep. 2003, Part II, pp. 711-716.
9. D. Honigmann, J. Ruisz, and H. Pottmann, "Fast Model Based Segmentation of Ultrasound Data using an Active Image", Proc. IEEE Int. Symp. on Biomedical Imaging, Washington DC, 2002, pp. 225-228.
10. N. Lin, W. Yu, J.S. Duncan, "Combinative Multi-scale Level Set Framework for Echocardiographic Image Segmentation", Medical Image Analysis, vol. 7, 2003, pp. 529-537.
11. S. Osher, J. Sethian, "Fronts Propagating with Curvature- Dependent Speed: Algorithms Based on the Hamilton-Jacobi Formulations", Journal Of Computational Physics, vol. 79, 1988, pp. 12-49.
12. D. Mumford, J. Shah, "Optimal Approximation by Piecewise Smooth Functions and Associated Variational Problems", Commun.Pure Appl. Math., vol.42, 1989, pp 577-685.
13. J.M. Morrel, S. Solimini, "Segmentation of Images by Variational Methods: A Constructive Approach", Madrid, Spain: Revista Matematica Universidad Computense de Madrid, vol.1, 1988, pp.169-182.
14. E. Papini et al, "Risk of Malignancy in Nonpalpable Thyroid Nodules: Predictive Value of Ultrasound and Color-Doppler Features", The Journal of Clinical Endocrinology & Metabolism, vol. 87, no.5, 2002, pp. 1941-1946.
15. M.R. Kaus, S.K. Warfield, F.A. Jolesz, R. Kikinis, "Segmentation of Meningiomas and Low Grade Gliomas in MRI", Proc. Second International Conference on Medical Image Computing and Computer-Assisted Intervention, Cambridge, England, 1999, pp. 1-10.
16. X. Hao, C. Bruce, C. Pislaru and J.F. Greeneaf, "A Novel Region Growing Method for segmenting ultrasound images", IEEE International Ultrasonics Symposium, Oct. 2000.