{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T22:42:10Z","timestamp":1742942530314,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":22,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811556784"},{"type":"electronic","value":"9789811556791"}],"license":[{"start":{"date-parts":[[2020,8,30]],"date-time":"2020-08-30T00:00:00Z","timestamp":1598745600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,8,30]],"date-time":"2020-08-30T00:00:00Z","timestamp":1598745600000},"content-version":"vor","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":[[2021]]},"DOI":"10.1007\/978-981-15-5679-1_68","type":"book-chapter","created":{"date-parts":[[2020,8,29]],"date-time":"2020-08-29T08:05:18Z","timestamp":1598688318000},"page":"701-710","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Image Assisted Assessment of Cancer Segment from Dermoscopy Images"],"prefix":"10.1007","author":[{"given":"M.","family":"Santhosh","sequence":"first","affiliation":[]},{"given":"R.","family":"Rubin Silas Raj","sequence":"additional","affiliation":[]},{"given":"V.","family":"Rajinikanth","sequence":"additional","affiliation":[]},{"given":"Suresh Chandra","family":"Satapathy","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,8,30]]},"reference":[{"key":"68_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2019.11.013","author":"A Bhandary","year":"2019","unstructured":"Bhandary, A., et al.: Deep-learning framework to detect lung abnormality\u2014a study with chest X-ray and lung CT scan images. Pattern Recogn. Lett. (2019). \nhttps:\/\/doi.org\/10.1016\/j.patrec.2019.11.013","journal-title":"Pattern Recogn. Lett."},{"key":"68_CR2","doi-asserted-by":"publisher","unstructured":"Fernandes, S.L., et al.: A reliable framework for accurate brain image examination and treatment planning based on early diagnosis support for clinicians. Neural Comput. Appl. 1\u201312 (2019). \nhttps:\/\/doi.org\/10.1007\/s00521-019-04369-5","DOI":"10.1007\/s00521-019-04369-5"},{"issue":"3","key":"68_CR3","doi-asserted-by":"publisher","first-page":"843","DOI":"10.1016\/j.bbe.2019.07.005","volume":"39","author":"N Dey","year":"2019","unstructured":"Dey, N., et al.: Social-Group-Optimization based tumor evaluation tool for clinical brain MRI of Flair\/diffusion-weighted modality. Biocybern. Biomed. Eng. 39(3), 843\u2013856 (2019). \nhttps:\/\/doi.org\/10.1016\/j.bbe.2019.07.005","journal-title":"Biocybern. Biomed. Eng."},{"key":"68_CR4","doi-asserted-by":"publisher","first-page":"302","DOI":"10.1007\/s10916-019-1428-9","volume":"43","author":"UR Acharya","year":"2019","unstructured":"Acharya, U.R., et al.: Automated detection of Alzheimer\u2019s disease using brain MRI images\u2014a study with various feature extraction techniques. J. Med. Syst. 43, 302 (2019). \nhttps:\/\/doi.org\/10.1007\/s10916-019-1428-9","journal-title":"J. Med. Syst."},{"key":"68_CR5","doi-asserted-by":"publisher","first-page":"101698","DOI":"10.1016\/j.artmed.2019.07.006","volume":"100","author":"V Jahmunah","year":"2019","unstructured":"Jahmunah, V., et al.: Automated detection of schizophrenia using nonlinear signal processing methods. Artif. Intell. Med. 100, 101698 (2019). \nhttps:\/\/doi.org\/10.1016\/j.artmed.2019.07.006","journal-title":"Artif. Intell. Med."},{"key":"68_CR6","doi-asserted-by":"publisher","unstructured":"Bhateja, V., Nigam, M., Bhadauria, A.S., Arya, A., Yu-Dong Zhang, Y-D.: Human visual system based optimized mathematical morphology approach for enhancement of brain MR images. J. Ambient. Intell. Humaniz. Comput. 1\u20139 (2019). \nhttps:\/\/doi.org\/10.1007\/s12652-019-01386-z","DOI":"10.1007\/s12652-019-01386-z"},{"issue":"8","key":"68_CR7","doi-asserted-by":"publisher","first-page":"3861","DOI":"10.1007\/s13369-018-3382-0","volume":"43","author":"SC Satapathy","year":"2018","unstructured":"Satapathy, S.C., El-Maleh, A., Bhateja, V.: Intelligent computing in multidisciplinary engineering applications. Arab. J. Sci. Eng. 43(8), 3861\u20133862 (2018)","journal-title":"Arab. J. Sci. Eng."},{"key":"68_CR8","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1016\/j.future.2017.12.006","volume":"82","author":"V Bhateja","year":"2018","unstructured":"Bhateja, V., Misra, M., Urooj, S.: Unsharp masking approaches for HVS based enhancement of mammographic masses: a comparative evaluation. Futur. Gener. Comput. Syst. 82, 176\u2013189 (2018)","journal-title":"Futur. Gener. Comput. Syst."},{"issue":"3","key":"68_CR9","doi-asserted-by":"publisher","first-page":"17","DOI":"10.4018\/IJACI.2019070102","volume":"10","author":"R Wang","year":"2019","unstructured":"Wang, R., Wang, G.: Web text categorization based on statistical merging algorithm in big data environment. Int. J. Ambient Comput. Intell. (IJACI) 10(3), 17\u201332 (2019). \nhttps:\/\/doi.org\/10.4018\/IJACI.2019070102","journal-title":"Int. J. Ambient Comput. Intell. (IJACI)"},{"issue":"3","key":"68_CR10","doi-asserted-by":"publisher","first-page":"92","DOI":"10.4018\/IJACI.2019070106","volume":"10","author":"Ali","year":"2019","unstructured":"Ali, et al.: Adam deep learning with SOM for human sentiment classification. Int. J. Ambient Comput. Intell. (IJACI) 10(3), 92\u2013116 (2019). \nhttps:\/\/doi.org\/10.4018\/IJACI.2019070106","journal-title":"Int. J. Ambient Comput. Intell. (IJACI)"},{"key":"68_CR11","doi-asserted-by":"publisher","unstructured":"Rajinikanth, V., Raja, N.S.M., Arunmozhi, S.: ABCD rule implementation for the skin melanoma assesment\u2014a study. In: IEEE International Conference on System, Computation, Automation and Networking (ICSCAN), pp. 1\u20134. IEEE (2019). \nhttps:\/\/doi.org\/10.1109\/icscan.2019.8878860","DOI":"10.1109\/icscan.2019.8878860"},{"key":"68_CR12","doi-asserted-by":"crossref","unstructured":"Amelard, R., Glaister, J., Wong, A., Clausi, D.A.: Melanoma decision support using lighting-corrected intuitive feature models. In: Computer Vision Techniques for the Diagnosis of Skin Cancer, Series in BioEngineering, pp. 193\u2013219 (2013)","DOI":"10.1007\/978-3-642-39608-3_7"},{"key":"68_CR13","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1016\/S0190-9622(94)70061-3","volume":"30","author":"F Nachbar","year":"1994","unstructured":"Nachbar, F., Stolz, W., Merckle, T., et al.: The ABCD rule of dermatoscopy: High prospective value in the diagnosis of doubtful melanocytic skin lesions. J. Am. Acad. Dermatol. 30, 551\u2013559 (1994)","journal-title":"J. Am. Acad. Dermatol."},{"issue":"2","key":"68_CR14","doi-asserted-by":"publisher","first-page":"51","DOI":"10.3390\/sym10020051","volume":"10","author":"N Dey","year":"2018","unstructured":"Dey, N., Rajinikanth, V., Ashour, A.S., Tavares, J.M.R.S.: Social group optimization supported segmentation and evaluation of skin melanoma images. Symmetry 10(2), 51 (2018). \nhttps:\/\/doi.org\/10.3390\/sym10020051","journal-title":"Symmetry"},{"key":"68_CR15","unstructured":"http:\/\/vip.uwaterloo.ca\/demos\/skin-cancer-detection"},{"key":"68_CR16","doi-asserted-by":"crossref","unstructured":"Amelard, R., Glaister, J.: Wong, A. and Clausi, D.A.: High-level intuitive features (HLIFs) for intuitive skin lesion description. IEEE Trans. Biomed. Eng.\u00a062(3), 820\u2013831 (2015)","DOI":"10.1109\/TBME.2014.2365518"},{"key":"68_CR17","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-016-2645-5","author":"SC Satapathy","year":"2016","unstructured":"Satapathy, S.C., Raja, N.S.M., Rajinikanth, V., Ashour, A.S.: Dey, N: Multi-level image thresholding using Otsu and chaotic bat algorithm. Neural Comput. Appl. (2016). \nhttps:\/\/doi.org\/10.1007\/s00521-016-2645-5","journal-title":"Neural Comput. Appl."},{"key":"68_CR18","volume-title":"Nature-Inspired Metaheuristic Algorithms","author":"XS Yang","year":"2011","unstructured":"Yang, X.S.: Nature-Inspired Metaheuristic Algorithms, 2nd edn. Luniver Press, Frome (2011)","edition":"2"},{"key":"68_CR19","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/0734-189X(85)90125-2","volume":"29","author":"JN Kapur","year":"1985","unstructured":"Kapur, J.N., Sahoo, P.K., Wong, A.K.C.: A new method for gray-level picture thresholding using the entropy of the histogram. Comput. Vis. Graph. Image Process. 29, 273\u2013285 (1985)","journal-title":"Comput. Vis. Graph. Image Process."},{"issue":"1","key":"68_CR20","doi-asserted-by":"publisher","first-page":"87","DOI":"10.4018\/IJACI.2020010105","volume":"11","author":"X Yang","year":"2020","unstructured":"Yang, X., Jiang, X.: A hybrid active contour model based on new edge-stop functions for image segmentation. Int. J. Ambient Comput. Intell. (IJACI) 11(1), 87\u201398 (2020). \nhttps:\/\/doi.org\/10.4018\/IJACI.2020010105","journal-title":"Int. J. Ambient Comput. Intell. (IJACI)"},{"key":"68_CR21","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1155\/2018\/3738049","volume":"2018","author":"SC Satapathy","year":"2018","unstructured":"Satapathy, S.C., Rajinikanth, V.: Jaya algorithm guided procedure to segment tumor from brain MRI. J. Optim. 2018, 12 (2018). \nhttps:\/\/doi.org\/10.1155\/2018\/3738049","journal-title":"J. Optim."},{"issue":"5","key":"68_CR22","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1109\/MCE.2019.2923926","volume":"8","author":"SL Fernandes","year":"2019","unstructured":"Fernandes, S.L., Rajinikanth, V., Kadry, S.: A hybrid framework to evaluate breast abnormality using infrared thermal images. IEEE Consum. Electron. Mag. 8(5), 31\u201336 (2019). \nhttps:\/\/doi.org\/10.1109\/MCE.2019.2923926","journal-title":"IEEE Consum. Electron. Mag."}],"container-title":["Advances in Intelligent Systems and Computing","Intelligent Data Engineering and Analytics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-15-5679-1_68","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,29]],"date-time":"2020-08-29T08:16:59Z","timestamp":1598689019000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-15-5679-1_68"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,30]]},"ISBN":["9789811556784","9789811556791"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-981-15-5679-1_68","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2020,8,30]]},"assertion":[{"value":"30 August 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}