• Journal of Infrared and Millimeter Waves
  • Vol. 39, Issue 6, 749 (2020)
Jian-Sheng WANG1、2, Qing-Li LI1、2、3、*, Mei ZHOU1、2, Li SUN1、2, Meng-Han HU1、2, Yue LYU1、2, and Jun-Hao CHU1、3
Author Affiliations
  • 1Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University, Shanghai200241, China
  • 2Engineering Center of SHMEC for Space Information and GNSS, Shanghai200241, China
  • 3Engineering Research Center of Nanophotonics & Advanced Instrument, Ministry of Education, East China Normal University, Shanghai200241, China
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    DOI: 10.11972/j.issn.1001-9014.2020.06.013 Cite this Article
    Jian-Sheng WANG, Qing-Li LI, Mei ZHOU, Li SUN, Meng-Han HU, Yue LYU, Jun-Hao CHU. Identification and measurement of cutaneous melanoma superficial spreading depth using microscopic hyperspectral imaging technology[J]. Journal of Infrared and Millimeter Waves, 2020, 39(6): 749 Copy Citation Text show less
    References

    [1] J Ferlay, I Soerjomataram, R Dikshit. Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012. International Journal of Cancer, 136, E359-E386(2015).

    [2] F Erdmann, J Lortet-Tieulent, J Schuz. International trends in the incidence of malignant melanoma 1953-2008uare recent generations at higher or lower risk?. International Journal of Cancer, 132, 385-400(2013).

    [3] V Gray-Schopfer, C Wellbrock, R Marais. Melanoma biology and new targeted therapy. Nature, 445, 851-857(2007).

    [4] A M M Eggermont, V Chiarion-Sileni, J J Grob. Prolonged Survival in Stage III Melanoma with Ipilimumab Adjuvant Therapy. New England Journal of Medicine, 375, 1845-1855(2016).

    [5] C Garbe, K Peris, A Hauschild. Diagnosis and treatment of melanoma. European consensus-based interdisciplinary guideline - Update 2016. European Journal of Cancer, 63, 201-217(2016).

    [6] L Thomas, S Puig. Dermoscopy, Digital Dermoscopy and Other Diagnostic Tools in the Early Detection of Melanoma and Follow-up of High-risk Skin Cancer Patients. Acta Dermato-Venereologica, 97, 14-21(2017).

    [7] L Q Yu, H Chen, Q Dou. Automated Melanoma Recognition in Dermoscopy Images via Very Deep Residual Networks. Ieee Transactions on Medical Imaging, 36, 994-1004(2017).

    [8] T Wang, G Hou, N Zhang. Melanoma Computer-aided Diagnosis Algorithms Based on Laser Scanning Confocal Microscope Images. Chinese Journal of Medical Imaging, 21, 130-133(2013).

    [9] M Rastrelli, S Tropea, C R Rossi. Melanoma: Epidemiology, Risk Factors, Pathogenesis, Diagnosis and Classification. In Vivo, 28, 1005-1011(2014).

    [10] M Silveira, J C Nascimento, J S Marques. Comparison of Segmentation Methods for Melanoma Diagnosis in Dermoscopy Images. Ieee Journal of Selected Topics in Signal Processing, 3, 35-45(2009).

    [11] M Binder, M Schwarz, A Winkler. Epiluminescence microscopy: A useful tool for the diagnosis of pigmented skin lesions for formally trained dermatologists. Archives of Dermatology, 131, 286-291(1995).

    [12] C Garbe, U Leiter. Melanoma epidemiology and trends. Clinics in Dermatology, 27, 3-9(2009).

    [13] R M MacKie, M Dunitz. Skin cancer : an illustrated guide to the aetiology. pathology and management of benign and malignant cutaneous tumours(1989).

    [14] M Mokhtari, M Rezaeian, S Gharibzadeh. Computer aided measurement of melanoma depth of invasion in microscopic images. Micron, 61, 40-48(2014).

    [15] N Noroozi, A Zakerolhosseini. Computerized measurement of melanocytic tumor depth in skin histopathological images. Micron, 77, 44-56(2015).

    [16] X Hongming, W Huiquan, R Berendt. Computerized measurement of melanoma depth of invasion in skin biopsy images. 2017 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), 17-20(2017).

    [17] M S Dinehart, S M Dinehart, S Sukpraprut-Braaten. Immunohistochemistry utilization in the diagnosis of melanoma. Journal of cutaneous pathology(2020).

    [18] K Kamyab-Hesary, A Ghanadan, K Balighi. Immunohistochemical Staining in the Assessment of Melanoma Tumor Thickness. Pathology oncology research : POR(2019).

    [19] 19ChopraA, SharmaR, RaoU N M. Pathology of Melanoma [J]. Surgical Clinics of North America, 2020, 100(1): 43-+.

    [20] G N Stamatas, C J Balas, N Kollias. Hyperspectral image acquisition and analysis of skin. Proceedings of the SPIE - The International Society for Optical Engineering, 4959, 77-82(2003).

    [21] T Nagaoka, A Nakamura, H Okutani. A possible melanoma discrimination index based on hyperspectral data: a pilot study. Skin Research and Technology, 18, 301-310(2012).

    [22] V Zheludev, I Polonen, N Neittaanmaki-Perttu. Delineation of malignant skin tumors by hyperspectral imaging using diffusion maps dimensionality reduction. Biomedical Signal Processing and Control, 16, 48-60(2015).

    [23] A Pardo, J A Gutierrez-Gutierrez, I Lihacova. On the spectral signature of melanoma: a non-parametric classification framework for cancer detection in hyperspectral imaging of melanocytic lesions. Biomedical Optics Express, 9, 6283-6301(2018).

    [24] A M Hosking, B J Coakley, D Chang. Hyperspectral imaging in automated digital dermoscopy screening for melanoma. Lasers in Surgery and Medicine, 51, 214-222(2019).

    [25] S V Panasyuk, S Yang, D V Faller. Medical hyperspectral imaging to facilitate residual tumor identification during surgery. Cancer Biology & Therapy, 6, 439-446(2007).

    [26] J S Wang, Q L Li. Quantitative analysis of liver tumors at different stages using microscopic hyperspectral imaging technology. Journal of Biomedical Optics, 23(2018).

    [27] G Zonios, L T Perelman, V M Backman. Diffuse reflectance spectroscopy of human adenomatous colon polyps in vivo. Applied Optics, 38, 6628-6637(1999).

    [28] S He, H Chen, F Jiao. Improved Preparation Method for Animal Histopathological Section. Progress in Veterinary Medicine, 32, 130-132(2011).

    [29] Q L Li, D R Xu, X F He. AOTF based molecular hyperspectral imaging system and its applications on nerve morphometry. Applied Optics, 52, 3891-3901(2013).

    [30] Q L Li, M Zhou, H Y Liu. Red Blood Cell Count Automation Using Microscopic Hyperspectral Imaging Technology. Applied Spectroscopy, 69, 1372-1380(2015).

    [31] Q L Li, Y T Wang, H Y Liu. A combined spatial-spectral method for automated white blood cells segmentation. Optics and Laser Technology, 54, 225-231(2013).

    [32] M L Huebschman, R A Schultz, H R Garner. Characteristics and capabilities of the Hyperspectral Imaging Microscope. Ieee Engineering in Medicine and Biology Magazine, 21, 104-117(2002).

    [33] A A Green, M Berman, P Switzer. A transformation for ordering multispectral data in terms of image quality with implications for noise removal. IEEE Transactions on Geoscience and Remote Sensing, 26, 65-74(1988).

    [34] L L Randeberg, E L Larsen, L O Svaasand. Characterization of vascular structures and skin bruises using hyperspectral imaging, image analysis and diffusion theory. Journal of Biophotonics, 3, 53-65(2010).

    [35] A A Nielsen. Kernel Maximum Autocorrelation Factor and Minimum Noise Fraction Transformations. Ieee Transactions on Image Processing, 20, 612-624(2011).

    [36] X Yang, X B Gao, D C Tao. An Efficient MRF Embedded Level Set Method for Image Segmentation. Ieee Transactions on Image Processing, 24, 9-21(2015).

    [37] B Wang, J Li, X Gao. An Edge-and Region-Based Level Set Method with Shape Priors for Image Segmentation. Chinese Journal of Computers, 35, 1067-1072(2012).

    [38] T F Chan, L A Vese. Active contours without edges. Ieee Transactions on Image Processing, 10, 266-277(2001).

    [39] B J de Kruif, T J A de Vries. Pruning error minimization in least squares support vector machines. Ieee Transactions on Neural Networks, 14, 696-702(2003).

    [40] D T Bui, T A Tuan, N D Hoang. Spatial prediction of rainfall-induced landslides for the Lao Cai area (Vietnam) using a hybrid intelligent approach of least squares support vector machines inference model and artificial bee colony optimization. Landslides, 14, 447-458(2017).

    [41] C-x Dong, X Rao, S-q Yang. Research on estimating the generalization performance of RBF-SVM. Journal of Xidian University, 31, 557-561(2004).

    [42] X Wei, X Yu, Q Fu. Spectral Matching Classification Approach and Experiment Combined with Spectral Angle Cosine and Spectral Correlation Coefficient. Geography and Geo-information Science, 32, 29-33(2016).

    [43] J G Elmore, R L Barnhill, D E Elder. Pathologists' diagnosis of invasive melanoma and melanocytic proliferations: observer accuracy and reproducibility study. Bmj-British Medical Journal, 357, 11(2017).

    Jian-Sheng WANG, Qing-Li LI, Mei ZHOU, Li SUN, Meng-Han HU, Yue LYU, Jun-Hao CHU. Identification and measurement of cutaneous melanoma superficial spreading depth using microscopic hyperspectral imaging technology[J]. Journal of Infrared and Millimeter Waves, 2020, 39(6): 749
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