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For: Filho M, Ma Z, Tavares JM. A Review of the Quantification and Classification of Pigmented Skin Lesions: From Dedicated to Hand-Held Devices. J Med Syst 2015;39:177. [PMID: 26411929 DOI: 10.1007/s10916-015-0354-8] [Cited by in Crossref: 61] [Cited by in F6Publishing: 29] [Article Influence: 8.7] [Reference Citation Analysis]
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7 Ünver HM, Ayan E. Skin Lesion Segmentation in Dermoscopic Images with Combination of YOLO and GrabCut Algorithm. Diagnostics (Basel) 2019;9:E72. [PMID: 31295856 DOI: 10.3390/diagnostics9030072] [Cited by in Crossref: 54] [Cited by in F6Publishing: 18] [Article Influence: 18.0] [Reference Citation Analysis]
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11 Kaushal M, Khehra BS, Akashdeep. Performance evaluation of fuzzy 2-partition entropy and big bang big crunch optimization based object detection and tracking approach. Multidim Syst Sign Process 2018;29:1579-611. [DOI: 10.1007/s11045-017-0515-7] [Cited by in Crossref: 1] [Article Influence: 0.2] [Reference Citation Analysis]
12 Irshad M, Muhammad N, Sharif M, Yasmeen M. Automatic segmentation of the left ventricle in a cardiac MR short axis image using blind morphological operation. Eur Phys J Plus 2018;133. [DOI: 10.1140/epjp/i2018-11941-0] [Cited by in Crossref: 21] [Cited by in F6Publishing: 3] [Article Influence: 5.3] [Reference Citation Analysis]
13 Han B, Wu Y. A novel active contour model based on modified symmetric cross entropy for remote sensing river image segmentation. Pattern Recognition 2017;67:396-409. [DOI: 10.1016/j.patcog.2017.02.022] [Cited by in Crossref: 26] [Cited by in F6Publishing: 7] [Article Influence: 5.2] [Reference Citation Analysis]
14 Diniz PHB, Valente TLA, Diniz JOB, Silva AC, Gattass M, Ventura N, Muniz BC, Gasparetto EL. Detection of white matter lesion regions in MRI using SLIC0 and convolutional neural network. Computer Methods and Programs in Biomedicine 2018;167:49-63. [DOI: 10.1016/j.cmpb.2018.04.011] [Cited by in Crossref: 13] [Cited by in F6Publishing: 10] [Article Influence: 3.3] [Reference Citation Analysis]
15 Zhou L, Zhang Z. An image segmentation method based on Mumford–Shah model with mask factor and neighborhood factor. Pattern Anal Applic 2020;23:85-94. [DOI: 10.1007/s10044-018-0730-3] [Reference Citation Analysis]
16 Golińska J, Sar‐pomian M, Rudnicka L. Dermoscopic features of psoriasis of the skin, scalp and nails – a systematic review. J Eur Acad Dermatol Venereol 2019;33:648-60. [DOI: 10.1111/jdv.15344] [Cited by in Crossref: 12] [Cited by in F6Publishing: 10] [Article Influence: 4.0] [Reference Citation Analysis]
17 Dey N, Rajinikanth V, Shi F, Tavares JMR, Moraru L, Arvind Karthik K, Lin H, Kamalanand K, Emmanuel C. Social-Group-Optimization based tumor evaluation tool for clinical brain MRI of Flair/diffusion-weighted modality. Biocybernetics and Biomedical Engineering 2019;39:843-56. [DOI: 10.1016/j.bbe.2019.07.005] [Cited by in Crossref: 37] [Cited by in F6Publishing: 2] [Article Influence: 12.3] [Reference Citation Analysis]
18 Kleczek P, Dyduch G, Graczyk-jarzynka A, Jaworek-korjakowska J. A New Approach to Border Irregularity Assessment with Application in Skin Pathology. Applied Sciences 2019;9:2022. [DOI: 10.3390/app9102022] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
19 Previtali F, Bertolazzi P, Felici G, Weitschek E. A novel method and software for automatically classifying Alzheimer’s disease patients by magnetic resonance imaging analysis. Computer Methods and Programs in Biomedicine 2017;143:89-95. [DOI: 10.1016/j.cmpb.2017.03.006] [Cited by in Crossref: 20] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
20 Claude LA, Houenou J, Duchesnay E, Favre P. Will machine learning applied to neuroimaging in bipolar disorder help the clinician? A critical review and methodological suggestions. Bipolar Disord 2020;22:334-55. [PMID: 32108409 DOI: 10.1111/bdi.12895] [Cited by in Crossref: 8] [Cited by in F6Publishing: 5] [Article Influence: 4.0] [Reference Citation Analysis]
21 Bozkurt F, Köse C, Sarı A. An inverse approach for automatic segmentation of carotid and vertebral arteries in CTA. Expert Systems with Applications 2018;93:358-75. [DOI: 10.1016/j.eswa.2017.10.041] [Cited by in Crossref: 9] [Article Influence: 2.3] [Reference Citation Analysis]
22 Del Rosario F, Farahi JM, Drendel J, Buntinx-Krieg T, Caravaglio J, Domozych R, Chapman S, Braunberger T, Dellavalle RP, Norris DA, Fathi R, Alkousakis T. Performance of a computer-aided digital dermoscopic image analyzer for melanoma detection in 1,076 pigmented skin lesion biopsies. J Am Acad Dermatol 2018;78:927-934.e6. [PMID: 29678380 DOI: 10.1016/j.jaad.2017.01.049] [Cited by in Crossref: 11] [Cited by in F6Publishing: 5] [Article Influence: 2.8] [Reference Citation Analysis]
23 Moghadas-dastjerdi H, Ahmadzadeh M, Karami E, Karami M, Samani A. Lung CT image based automatic technique for COPD GOLD stage assessment. Expert Systems with Applications 2017;85:194-203. [DOI: 10.1016/j.eswa.2017.05.036] [Cited by in Crossref: 4] [Cited by in F6Publishing: 1] [Article Influence: 0.8] [Reference Citation Analysis]
24 Dakua SP, Abinahed J, Al-ansari A. A PCA-based approach for brain aneurysm segmentation. Multidim Syst Sign Process 2018;29:257-77. [DOI: 10.1007/s11045-016-0464-6] [Cited by in Crossref: 7] [Cited by in F6Publishing: 1] [Article Influence: 1.2] [Reference Citation Analysis]
25 Dey N, Rajinikanth V, Ashour A, Tavares JM. Social Group Optimization Supported Segmentation and Evaluation of Skin Melanoma Images. Symmetry 2018;10:51. [DOI: 10.3390/sym10020051] [Cited by in Crossref: 79] [Cited by in F6Publishing: 8] [Article Influence: 19.8] [Reference Citation Analysis]
26 Wahba MA, Ashour AS, Guo Y, Napoleon SA, Elnaby MMA. A novel cumulative level difference mean based GLDM and modified ABCD features ranked using eigenvector centrality approach for four skin lesion types classification. Computer Methods and Programs in Biomedicine 2018;165:163-74. [DOI: 10.1016/j.cmpb.2018.08.009] [Cited by in Crossref: 17] [Cited by in F6Publishing: 5] [Article Influence: 4.3] [Reference Citation Analysis]
27 Muangkote N, Sunat K, Chiewchanwattana S. R r-cr -IJADE: An efficient differential evolution algorithm for multilevel image thresholding. Expert Systems with Applications 2017;90:272-89. [DOI: 10.1016/j.eswa.2017.08.029] [Cited by in Crossref: 14] [Cited by in F6Publishing: 3] [Article Influence: 2.8] [Reference Citation Analysis]
28 Pare S, Bhandari AK, Kumar A, Bajaj V. Backtracking search algorithm for color image multilevel thresholding. SIViP 2018;12:385-92. [DOI: 10.1007/s11760-017-1170-z] [Cited by in Crossref: 15] [Cited by in F6Publishing: 7] [Article Influence: 3.0] [Reference Citation Analysis]
29 Pathan S, Prabhu KG, Siddalingaswamy P. Techniques and algorithms for computer aided diagnosis of pigmented skin lesions—A review. Biomedical Signal Processing and Control 2018;39:237-62. [DOI: 10.1016/j.bspc.2017.07.010] [Cited by in Crossref: 99] [Cited by in F6Publishing: 29] [Article Influence: 24.8] [Reference Citation Analysis]
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33 Roja Ramani D, Ranjani SS. An Efficient Melanoma Diagnosis Approach Using Integrated HMF Multi-Atlas Map Based Segmentation. J Med Syst 2019;43:225. [PMID: 31190229 DOI: 10.1007/s10916-019-1315-4] [Cited by in Crossref: 1] [Article Influence: 0.3] [Reference Citation Analysis]
34 Fu T, Li Q, Zhu J, Ai D, Huang Y, Song H, Jiang Y, Wang Y, Yang J. Sparse deformation prediction using Markove Decision Processes (MDP) for Non-rigid registration of MR image. Comput Methods Programs Biomed 2018;162:47-59. [PMID: 29903494 DOI: 10.1016/j.cmpb.2018.04.024] [Cited by in Crossref: 6] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
35 Kumar SN, Fred AL, Varghese PS. An Overview of Segmentation Algorithms for the Analysis of Anomalies on Medical Images. Journal of Intelligent Systems 2018;29:612-25. [DOI: 10.1515/jisys-2017-0629] [Cited by in Crossref: 10] [Cited by in F6Publishing: 1] [Article Influence: 2.5] [Reference Citation Analysis]
36 Maglogiannis I, Kontogianni G, Papadodima O, Karanikas H, Billiris A, Chatziioannou A. An Integrated Platform for Skin Cancer Heterogenous and Multilayered Data Management. J Med Syst 2021;45:10. [PMID: 33404959 DOI: 10.1007/s10916-020-01679-3] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
37 Ma Z, Tavares JMR. Effective features to classify skin lesions in dermoscopic images. Expert Systems with Applications 2017;84:92-101. [DOI: 10.1016/j.eswa.2017.05.003] [Cited by in Crossref: 32] [Cited by in F6Publishing: 12] [Article Influence: 6.4] [Reference Citation Analysis]
38 Ashour AS, Wahba MA, El-Wahab BSA, Guo Y, Hawas AR. An embedded novel compact feature profile image in speech signal for teledermoscopy system. Health Inf Sci Syst 2020;8:23. [PMID: 32626574 DOI: 10.1007/s13755-020-00113-9] [Reference Citation Analysis]