Abstract
This paper investigates a 3D novel dual active contours approach to segment multiple regions in medical images. The locally based segmentation approaches can handle the heterogeneity of the image as well as the noise artefacts. In this light, a locally based dual active contours approach is proposed to separate among three regions constituting the image. The dual contours approach combines the local information along each point in the two curves conjointly with the information between them. Different parameters in this approach determine its accuracy, including the initial distance between the two curves and how much local the information is used in each curve. The approach’s efficiency is evaluated on synthetic images as well as HRpQCT and MRI data compared to state-of-the-art techniques. The computational cost of this approach is reduced using the convolution operator and the FFT transform. The experimental evaluation of the approach demonstrates its segmentation performance on synthetic images and real medical images.
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Ma Z, Jorge RMN, Mascarenhas T, Tavares JMRS (2013) Segmentation of female pelvic organs in axial magnetic resonance images using coupled geometric deformable models. Comput Biol Med 43(4):248–258
Buie HR, Campbell GM, Klinck RJ, MacNeil JA, Boyd SK (2007) Automatic segmentation of cortical and trabecular compartments based on a dual threshold technique for in vivo micro-CT bone analysis. Bone 41(4):505–515
Burghardt AJ, Buie HR, Laib A, Majumdar S, Boyd SK (2010) Reproducibility of direct quantitative measures of cortical bone microarchitecture of the distal radius and tibia by HR-pQCT. Bone 47(3):519–528
Valentinitsch A, Patsch JM, Deutschmann J, Schueller-Weidekamm C, Resch H, Kainberger F, Langs G (2012) Automated threshold-independent cortex segmentation by 3d-texture analysis of HR-pQCT scans. Bone 51(3):480–487
Zebaze R, Ghasem-Zadeh A, Mbala A, Seeman E (2013) A new method of segmentation of compact-appearing, transitional and trabecular compartments and quantification of cortical porosity from high resolution peripheral quantitative computed tomographic images. Bone 54(1):8–20
Kass M, Witkin A, Terzopoulos D (1988) Snakes: active contour models. Int J Comput Vis 1(4):321–331
Truc PTH, Lee S, Kim T-S (2008) A density distance augmented Chan–Vese active contour for CT bone segmentation. In: Conference proceedings: annual international conference of the IEEE engineering in medicine and biology society. IEEE Engineering in Medicine and Biology Society. vol 2008, pp 482–5
Sebastian TB, Tek H, Crisco JJ, Kimia BB (2003) Segmentation of carpal bones from CT images using skeletally coupled deformable models. Med Image Anal 7(1):21–45
Caselles V, Catt F, Coll T, Dibos F (1993) A geometric model for active contours in image processing. Numer Math 66(1):1–31
Caselles V, Kimmel R, Sapiro G (1997) Geodesic active contours. Int J Comput Vis 22(1):61–79
Chan TF, Vese LA (2001) Active contours without edges. IEEE Trans Image Process 10(2):266–277
Chen Z, Qiu T, Ruan S (2008 Oct) Fuzzy adaptive level set algorithm for brain tissue segmentation. In: IEEE 9th international conference on signal processing, Bei**g, China
Krinidis S, Chatzis V (2009) Fuzzy energy-based active contours. IEEE Trans Image Process 18(12):2747–2755
Shyu K-K, Pham V-T, Tran T-T, Lee P-L (2011) Global and local fuzzy energy-based active contours for image segmentation. Nonlinear Dyn 67(2):1559–1578
Hafri M, Toumi H, Boutroy S, Chapurlat RD, Lespessailles E, Jennane R (dec 2016) Fuzzy energy based active contours model for HR-PQCT cortical bone segmentation. In: 2016 IEEE international conference on image processing (ICIP), pp 4334–4338
Lankton S, Tannenbaum A (2008) Localizing region-based active contours. IEEE Trans Image Process 17(11):2029–2039
Yezzi Jr. A, Tsai A, Willsky A (1999) A statistical approach to snakes for bimodal and trimodal imagery. In: Proceedings of the international conference on computer vision-ser. ICCV ’99, vol 2. IEEE Computer Society, Washington, DC, USA, pp 898
Yezzi A, Tsai A, Willsky A (2002) A fully global approach to image segmentation via coupled curve evolution equations. J Vis Comun Image Represent 13(1):195–216
Ma Z, Jorge RN, Mascarenhas T, Tavares JMRS (2011) Novel approach to segment the inner and outer boundaries of the bladder wall in T2-weighted magnetic resonance images. Ann Biomed Eng 39(8):2287–2297
Gao X, Wang B, Tao D, Li X (2011) A relay level set method for automatic image segmentation. IEEE Trans Syst Man Cybernet Part B (Cybernetics) 41(2):518–525
Hafri M, Toumi E, Lespessailles Hechmi, Jennane R (2016 Dec) Dual active contours model for HR-PQCT cortical bone segmentation. In: 2016 International conference on pattern recognition (ICPR)
Li C, Kao C-Y, Gore J, Ding Z (2008) Minimization of region-scalable fitting energy for image segmentation. IEEE Trans Image Process 17(10):1940–1949
Sussman M, Smereka P, Osher S (1994) A level set approach for computing solutions to incompressible two-phase flow. J Comput Phys 114(1):146–159
Brodatz P (1966) Textures: a photographic album for artists and designers. Dover Publications, New York
Dice LR (1945) Measures of the amount of ecologic association between species. Ecology 26(3):297
Aspert N, Santa Cruz D, Ebrahimi T (2002) Mesh: measuring errors between surfaces using the hausdorff distance. Int Conf Multimed ExpoICME 1:705–708
Yushkevich PA, Piven J, Hazlett HC, Smith RG, Ho S, Gee JC, Gerig G (2006) User-guided 3d active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage 31(3):1116–1128
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Hafri, M., Toumi, H., Lespessailles, E. et al. A novel 3D dual active contours approach. Pattern Anal Applic 23, 581–591 (2020). https://doi.org/10.1007/s10044-019-00796-1
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DOI: https://doi.org/10.1007/s10044-019-00796-1