{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T21:03:34Z","timestamp":1762376614900},"publisher-location":"Singapore","reference-count":47,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789813292901"},{"type":"electronic","value":"9789813292918"}],"license":[{"start":{"date-parts":[[2019,9,20]],"date-time":"2019-09-20T00:00:00Z","timestamp":1568937600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-981-32-9291-8_10","type":"book-chapter","created":{"date-parts":[[2019,9,19]],"date-time":"2019-09-19T14:07:48Z","timestamp":1568902068000},"page":"115-126","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A Novel Deep Learning Approach for the Removal of Speckle Noise from Optical Coherence Tomography Images Using Gated Convolution\u2013Deconvolution Structure"],"prefix":"10.1007","author":[{"given":"Sandeep N.","family":"Menon","sequence":"first","affiliation":[]},{"given":"V. B.","family":"Vineeth Reddy","sequence":"additional","affiliation":[]},{"given":"A.","family":"Yeshwanth","sequence":"additional","affiliation":[]},{"given":"B. N.","family":"Anoop","sequence":"additional","affiliation":[]},{"given":"Jeny","family":"Rajan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,9,20]]},"reference":[{"issue":"1\u20132","key":"10_CR1","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1038\/sj.neo.7900071","volume":"2","author":"JG Fujimoto","year":"2000","unstructured":"Fujimoto, J.G., Pitris, C., Boppart, S.A., Brezinski, M.E.: Optical coherence tomography: an emerging technology for biomedical imaging and optical biopsy. Neoplasia 2(1\u20132), 9\u201325 (2000)","journal-title":"Neoplasia"},{"issue":"9","key":"10_CR2","doi-asserted-by":"publisher","first-page":"3903","DOI":"10.1364\/BOE.8.003903","volume":"8","author":"M Li","year":"2017","unstructured":"Li, M., Idoughi, R., Choudhury, B., Heidrich, W.: Statistical model for OCT image denoising. Biomed. Opt. Express 8(9), 3903\u20133917 (2017)","journal-title":"Biomed. Opt. Express"},{"issue":"8","key":"10_CR3","doi-asserted-by":"publisher","first-page":"8338","DOI":"10.1364\/OE.18.008338","volume":"18","author":"A Wong","year":"2010","unstructured":"Wong, A., Mishra, A., Bizheva, K., Clausi, D.A.: General Bayesian estimation for speckle noise reduction in optical coherence tomography retinal imagery. Opt. Express 18(8), 8338\u20138352 (2010)","journal-title":"Opt. Express"},{"key":"10_CR4","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1016\/j.compbiomed.2016.02.003","volume":"71","author":"P Sudeep","year":"2016","unstructured":"Sudeep, P., Niwas, S.I., Palanisamy, P., Rajan, J., Xiaojun, Y., Wang, X., Luo, Y., Liu, L.: Enhancement and bias removal of optical coherence tomography images: an iterative approach with adaptive bilateral filtering. Comput. Biol. Med. 71, 97\u2013107 (2016)","journal-title":"Comput. Biol. Med."},{"issue":"11","key":"10_CR5","doi-asserted-by":"publisher","first-page":"1483","DOI":"10.1109\/TMI.2006.881376","volume":"25","author":"Z Tao","year":"2006","unstructured":"Tao, Z., Tagare, H.D., Beaty, J.D.: Evaluation of four probability distribution models for speckle in clinical cardiac ultrasound images. IEEE Trans. Med. Imaging 25(11), 1483\u20131491 (2006)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"8","key":"10_CR6","first-page":"086011","volume":"22","author":"Z Amini","year":"2017","unstructured":"Amini, Z., Rabbani, H.: Optical coherence tomography image denoising using Gaussianization transform. J. Biomed. Opt. 22(8), 086011 (2017)","journal-title":"J. Biomed. Opt."},{"issue":"3","key":"10_CR7","doi-asserted-by":"publisher","first-page":"035012","DOI":"10.1088\/2057-1976\/2\/3\/035012","volume":"2","author":"H Rajabi","year":"2016","unstructured":"Rajabi, H., Zirak, A.: Speckle noise reduction and motion artifact correction based on modified statistical parameters estimation in OCT images. Biomed. Phys. Eng. Express 2(3), 035012 (2016)","journal-title":"Biomed. Phys. Eng. Express"},{"key":"10_CR8","doi-asserted-by":"crossref","unstructured":"Meiniel, W.,\u00a0Gan, Y., Olivo-Marin, J.-C.,\u00a0Angelini, E.: A sparsity-based simplification method for segmentation of spectral-domain optical coherence tomography images. In: Wavelets and Sparsity XVII, vol. 10394, p. 1039406. International Society for Optics and Photonics (2017)","DOI":"10.1117\/12.2274126"},{"key":"10_CR9","unstructured":"Isar, C.S.-C.A.: Optical coherence tomography speckle reduction in the wavelets domain. Editorial Board 3"},{"issue":"5","key":"10_CR10","doi-asserted-by":"publisher","first-page":"056009","DOI":"10.1117\/1.JBO.19.5.056009","volume":"19","author":"Y Du","year":"2014","unstructured":"Du, Y., Liu, G., Feng, G., Chen, Z.: Speckle reduction in optical coherence tomography images based on wave atoms. J. Biomed. Opt. 19(5), 056009 (2014)","journal-title":"J. Biomed. Opt."},{"issue":"3","key":"10_CR11","doi-asserted-by":"publisher","first-page":"572","DOI":"10.1364\/BOE.3.000572","volume":"3","author":"MA Mayer","year":"2012","unstructured":"Mayer, M.A., Borsdorf, A., Wagner, M., Hornegger, J., Mardin, C.Y., Tornow, R.P.: Wavelet denoising of multiframe optical coherence tomography data. Biomed. Opt. Express 3(3), 572\u2013589 (2012)","journal-title":"Biomed. Opt. Express"},{"issue":"22","key":"10_CR12","doi-asserted-by":"publisher","first-page":"8901","DOI":"10.1088\/0031-9155\/60\/22\/8901","volume":"60","author":"J Duan","year":"2015","unstructured":"Duan, J., Tench, C., Gottlob, I., Proudlock, F., Bai, L.: New variational image decomposition model for simultaneously denoising and segmenting optical coherence tomography images. Phys. Med. Biol. 60(22), 8901 (2015)","journal-title":"Phys. Med. Biol."},{"key":"10_CR13","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.bspc.2015.09.012","volume":"24","author":"J Duan","year":"2016","unstructured":"Duan, J., Lu, W., Tench, C., Gottlob, I., Proudlock, F., Samani, N.N., Bai, L.: Denoising optical coherence tomography using second order total generalized variation decomposition. Biomed. Signal Process. Control 24, 120\u2013127 (2016)","journal-title":"Biomed. Signal Process. Control"},{"issue":"19","key":"10_CR14","doi-asserted-by":"publisher","first-page":"7809","DOI":"10.1016\/j.ijleo.2016.05.088","volume":"127","author":"H Ren","year":"2016","unstructured":"Ren, H., Qin, L., Zhu, X.: Speckle reduction and cartoon-texture decomposition of ophthalmic optical coherence tomography images by variational image decomposition. Optik-Int. J. Light Electron Opt. 127(19), 7809\u20137821 (2016)","journal-title":"Optik-Int. J. Light Electron Opt."},{"key":"10_CR15","unstructured":"Varnousfaderani, E.S., Vogl, W.-D.,\u00a0Wu, J., Gerendas, B.S.,\u00a0Simader, C.,\u00a0Langs, G., Waldstein, S.M.,\u00a0Schmidt-Erfurth, U.: Geodesic denoising for optical coherence tomography images. In: Medical Imaging 2016: Image Processing, vol. 9784, p. 97840K. International Society for Optics and Photonics (2016)"},{"issue":"13","key":"10_CR16","doi-asserted-by":"publisher","first-page":"D43","DOI":"10.1364\/AO.54.000D43","volume":"54","author":"J Aum","year":"2015","unstructured":"Aum, J., Kim, J.-H., Jeong, J.: Effective speckle noise suppression in optical coherence tomography images using nonlocal means denoising filter with double Gaussian anisotropic kernels. Appl. Opt. 54(13), D43\u2013D50 (2015)","journal-title":"Appl. Opt."},{"issue":"3","key":"10_CR17","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1007\/s10278-014-9742-8","volume":"28","author":"Q Chen","year":"2015","unstructured":"Chen, Q., de Sisternes, L., Leng, T., Rubin, D.L.: Application of improved homogeneity similarity-based denoising in optical coherence tomography retinal images. J. Digit. Imaging 28(3), 346\u2013361 (2015)","journal-title":"J. Digit. Imaging"},{"key":"10_CR18","doi-asserted-by":"crossref","unstructured":"Liu, X.,\u00a0Yang, Z.,\u00a0Wang, J.: A novel noise reduction method for optical coherence tomography images. In: International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), pp. 167\u2013171. IEEE (2016)","DOI":"10.1109\/CISP-BMEI.2016.7852702"},{"issue":"6","key":"10_CR19","doi-asserted-by":"publisher","first-page":"526","DOI":"10.1016\/j.compmedimag.2014.06.012","volume":"38","author":"N Anantrasirichai","year":"2014","unstructured":"Anantrasirichai, N., Nicholson, L., Morgan, J.E., Erchova, I., Mortlock, K., North, R.V., Albon, J., Achim, A.: Adaptive-weighted bilateral filtering and other pre-processing techniques for optical coherence tomography. Comput. Med. Imaging Graph. 38(6), 526\u2013539 (2014)","journal-title":"Comput. Med. Imaging Graph."},{"key":"10_CR20","doi-asserted-by":"crossref","unstructured":"Liu, G.,\u00a0Wang, Z.,\u00a0Mu, G.,\u00a0Li, P.: Efficient OCT image enhancement based on collaborative shock filtering. J. Healthc. Eng. (2018)","DOI":"10.1155\/2018\/7329548"},{"key":"10_CR21","doi-asserted-by":"crossref","unstructured":"Baghaie, A., D\u2019souza, R.M.,\u00a0Yu, Z.: Sparse and low rank decomposition based batch image alignment for speckle reduction of retinal OCT images. In: 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), pp. 226\u2013230. IEEE (2015)","DOI":"10.1109\/ISBI.2015.7163855"},{"issue":"3","key":"10_CR22","doi-asserted-by":"publisher","first-page":"035603","DOI":"10.1088\/1612-2011\/10\/3\/035603","volume":"10","author":"F Luan","year":"2013","unstructured":"Luan, F., Wu, Y.: Application of RPCA in optical coherence tomography for speckle noise reduction. Laser Phys. Lett. 10(3), 035603 (2013)","journal-title":"Laser Phys. Lett."},{"issue":"11","key":"10_CR23","doi-asserted-by":"publisher","first-page":"2034","DOI":"10.1109\/TMI.2013.2271904","volume":"32","author":"L Fang","year":"2013","unstructured":"Fang, L., Li, S., McNabb, R.P., Nie, Q., Kuo, A.N., Toth, C.A., Izatt, J.A., Farsiu, S.: Fast acquisition and reconstruction of optical coherence tomography images via sparse representation. IEEE Trans. Med. Imaging 32(11), 2034\u20132049 (2013)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"10_CR24","unstructured":"Cheng, J.,\u00a0Duan, L., Wong, D.W.K.,\u00a0Akiba, M.,\u00a0Liu, J.: Speckle reduction in optical coherence tomography by matrix completion using bilateral random projection. In: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 186\u2013189. IEEE (2014)"},{"key":"10_CR25","unstructured":"Zhao, A.: Image denoising with deep convolutional neural networks"},{"key":"10_CR26","unstructured":"Cho, K.: Boltzmann machines and denoising autoencoders for image denoising. \n                  arXiv:1301.3468"},{"key":"10_CR27","unstructured":"Xie, J.,\u00a0Xu, L.,\u00a0Chen, E.: Image denoising and inpainting with deep neural networks. In: Advances in Neural Information Processing Systems, pp. 341\u2013349 (2012)"},{"key":"10_CR28","unstructured":"Agostinelli, F., Anderson, M.R.,\u00a0Lee, H.: Adaptive multi-column deep neural networks with application to robust image denoising. In: Advances in Neural Information Processing Systems, pp. 1493\u20131501 (2013)"},{"issue":"7","key":"10_CR29","doi-asserted-by":"publisher","first-page":"3142","DOI":"10.1109\/TIP.2017.2662206","volume":"26","author":"K Zhang","year":"2017","unstructured":"Zhang, K., Zuo, W., Chen, Y., Meng, D., Zhang, L.: Beyond a Gaussian denoiser: residual learning of deep CNN for image denoising. IEEE Trans. Image Process. 26(7), 3142\u20133155 (2017)","journal-title":"IEEE Trans. Image Process."},{"key":"10_CR30","unstructured":"Mao, X.-J.,\u00a0Shen, C., Yang, Y.-B.: Image restoration using convolutional auto-encoders with symmetric skip connections. \n                  arXiv:1606.08921"},{"key":"10_CR31","unstructured":"Mao, X.,\u00a0Shen, C., Yang, Y.-B.: Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections. In: Advances in Neural Information Processing Systems, pp. 2802\u20132810 (2016)"},{"key":"10_CR32","doi-asserted-by":"crossref","unstructured":"Kim, M.,\u00a0Smaragdis, P.: Adaptive denoising autoencoders: a fine-tuning scheme to learn from test mixtures. In: International Conference on Latent Variable Analysis and Signal Separation, pp. 100\u2013107. Springer (2015)","DOI":"10.1007\/978-3-319-22482-4_12"},{"key":"10_CR33","doi-asserted-by":"crossref","unstructured":"Gondara, L.: Medical image denoising using convolutional denoising autoencoders. In: 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW), pp. 241\u2013246. IEEE (2016)","DOI":"10.1109\/ICDMW.2016.0041"},{"issue":"1","key":"10_CR34","first-page":"69","volume":"70","author":"Y Murali","year":"2015","unstructured":"Murali, Y., Babu, M., Subramanyam, M., Giriprasad, M.: A modified BM3D algorithm for SAR image despeckling. Procedia Comput. Sci. (Elsevier) 70(1), 69\u201375 (2015)","journal-title":"Procedia Comput. Sci. (Elsevier)"},{"issue":"11","key":"10_CR35","doi-asserted-by":"publisher","first-page":"6858","DOI":"10.1109\/TGRS.2014.2304298","volume":"52","author":"L Xu","year":"2014","unstructured":"Xu, L., Li, J., Shu, Y., Peng, J.: SAR image denoising via clustering-based principal component analysis. IEEE Trans. Geosci. Remote Sens. 52(11), 6858\u20136869 (2014)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"2","key":"10_CR36","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1109\/TGRS.2011.2161586","volume":"50","author":"S Parrilli","year":"2012","unstructured":"Parrilli, S., Poderico, M., Angelino, C.V., Verdoliva, L.: A nonlocal SAR image denoising algorithm based on LLMMSE wavelet shrinkage. IEEE Trans. Geosci. Remote Sens. 50(2), 606\u2013616 (2012)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"8","key":"10_CR37","doi-asserted-by":"publisher","first-page":"1773","DOI":"10.1109\/TGRS.2003.813488","volume":"41","author":"A Achim","year":"2003","unstructured":"Achim, A., Tsakalides, P., Bezerianos, A.: SAR image denoising via Bayesian wavelet shrinkage based on heavy-tailed modeling. IEEE Trans. Geosci. Remote Sens. 41(8), 1773\u20131784 (2003)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10_CR38","unstructured":"Kovaci, M.,\u00a0Isar, D.,\u00a0Isar, A.: Denoising SAR images. In: International Symposium on Signals, Circuits and Systems, 2003. SCS 2003, vol.\u00a01, pp. 281\u2013284. IEEE (2003)"},{"key":"10_CR39","unstructured":"Chierchia, G.,\u00a0Cozzolino, D.,\u00a0Poggi, G.,\u00a0Verdoliva, L.: SAR image despeckling through convolutional neural networks. \n                  arXiv:1704.00275"},{"key":"10_CR40","doi-asserted-by":"crossref","unstructured":"Hore, A.,\u00a0Ziou, D.: Image quality metrics: PSNR vs. SSIM. In: 2010 20th International Conference on Pattern Recognition (ICPR), pp. 2366\u20132369. IEEE (2010)","DOI":"10.1109\/ICPR.2010.579"},{"key":"10_CR41","unstructured":"OPTIMA cyst segmentation challenge (2015). \n                  https:\/\/optima.meduniwien.ac.at\/research\/challenges\/"},{"issue":"1","key":"10_CR42","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1007\/BF02613934","volume":"16","author":"SD Dubey","year":"1970","unstructured":"Dubey, S.D.: Compound gamma, beta and f distributions. Metrika 16(1), 27\u201331 (1970)","journal-title":"Metrika"},{"issue":"10","key":"10_CR43","doi-asserted-by":"publisher","first-page":"2221","DOI":"10.1109\/TIP.2009.2024064","volume":"18","author":"P Coup\u00e9","year":"2009","unstructured":"Coup\u00e9, P., Hellier, P., Kervrann, C., Barillot, C.: Nonlocal means-based speckle filtering for ultrasound images. IEEE Trans. Image Process. 18(10), 2221\u20132229 (2009)","journal-title":"IEEE Trans. Image Process."},{"issue":"21","key":"10_CR44","doi-asserted-by":"publisher","first-page":"1856","DOI":"10.1080\/09500340.2015.1068392","volume":"62","author":"D Thapa","year":"2015","unstructured":"Thapa, D., Raahemifar, K., Lakshminarayanan, V.: Reduction of speckle noise from optical coherence tomography images using multi-frame weighted nuclear norm minimization method. J. Modern Opt. 62(21), 1856\u20131864 (2015)","journal-title":"J. Modern Opt."},{"key":"10_CR45","unstructured":"Fisher, Y.: Fractal Image Compression: Theory and Application. Springer Science & Business Media (2012)"},{"issue":"4","key":"10_CR46","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"key":"10_CR47","doi-asserted-by":"publisher","unstructured":"Girish, G., Kothari, A.R.,\u00a0Rajan, J.: Marker controlled watershed transform for intra-retinal cysts segmentation from optical coherence tomography B-scans. Pattern Recognit. Lett. \n                  https:\/\/doi.org\/10.1016\/j.patrec.2017.12.019\n                  \n                . \n                  http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0167865517304658","DOI":"10.1016\/j.patrec.2017.12.019"}],"container-title":["Advances in Intelligent Systems and Computing","Proceedings of 3rd International Conference on Computer Vision and Image Processing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-32-9291-8_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,19]],"date-time":"2019-09-19T14:09:12Z","timestamp":1568902152000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-32-9291-8_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,20]]},"ISBN":["9789813292901","9789813292918"],"references-count":47,"URL":"https:\/\/doi.org\/10.1007\/978-981-32-9291-8_10","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2019,9,20]]},"assertion":[{"value":"20 September 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}