{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T12:10:09Z","timestamp":1744200609129,"version":"3.40.3"},"reference-count":107,"publisher":"Springer Science and Business Media LLC","issue":"10","license":[{"start":{"date-parts":[[2022,2,25]],"date-time":"2022-02-25T00:00:00Z","timestamp":1645747200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,2,25]],"date-time":"2022-02-25T00:00:00Z","timestamp":1645747200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2022,4]]},"DOI":"10.1007\/s11042-022-12450-w","type":"journal-article","created":{"date-parts":[[2022,2,25]],"date-time":"2022-02-25T13:02:47Z","timestamp":1645794167000},"page":"14217-14245","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Epidemiological Mucormycosis treatment and diagnosis challenges using the adaptive properties of computer vision techniques based approach: a review"],"prefix":"10.1007","volume":"81","author":[{"family":"Nira","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2098-4196","authenticated-orcid":false,"given":"Harekrishna","family":"Kumar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,2,25]]},"reference":[{"key":"12450_CR1","doi-asserted-by":"crossref","unstructured":"Abbas A, Abdelsamea MM, Gaber MM (2020) Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network. arXiv preprint arXiv:2003.13815","DOI":"10.1101\/2020.03.30.20047456"},{"issue":"1","key":"12450_CR2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0244416","volume":"16","author":"M Abd Elaziz","year":"2021","unstructured":"Abd Elaziz M, AA Alqaness M, Abo Zaid EO, Lu S, Ali Ibrahim R, A Ewees A (2021) Automatic clustering method to segment COVID-19 CT images. PLoS One 16(1):e0244416","journal-title":"PLoS One"},{"issue":"11","key":"12450_CR3","doi-asserted-by":"publisher","first-page":"2274","DOI":"10.1109\/TPAMI.2012.120","volume":"34","author":"R Achanta","year":"2012","unstructured":"Achanta R, Shaji A, Smith K, Lucchi A, Fua P, S\u00fcsstrunk S (2012) SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274\u20132282","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"12450_CR4","unstructured":"Acharjya PP, Das R, Ghoshal D (2012) Study and comparison of different edge detectors for image segmentation. Global Journal of Computer Science and Technology"},{"key":"12450_CR5","unstructured":"Adil A (2021) Over 28,200 \u2018black fungus\u2019 cases recorded in India. Anadolu agency, 2021. https:\/\/www.aa.com.tr\/en\/asia-pacific\/over-28-200-black-fungus-cases-recorded-in-india\/2266396. Accessed 6.21.21"},{"key":"12450_CR6","unstructured":"After black fungus and white fungus, another fungal infection aspergillosis, hits India (n.d.). [online]. Available: https:\/\/www.dnaindia.com\/india\/report-after-black-fungus-and-white-fungus-another-fungal-infection-aspergillosis-hits-india-2892150. Accessed 3 Mar 2021"},{"key":"12450_CR7","unstructured":"After Black, White Or Yellow Fungus \u2013 Aspergillosis Is The New Fungal Infection Reported In Covid-19 Patients In India (n.d.). [online]. Available: https:\/\/thenationalbulletin.in\/after-black-white-or-yellow-fungus-ndash-aspergillosis-is-the-new-fungal-infection-reported-in-covid-19-patients-in-india. Accessed 3 Mar 2021"},{"key":"12450_CR8","unstructured":"AI Helps Doctors Diagnose the Coronavirus. (n.d.) [Online]. Available: https:\/\/news.developer.nvidia.com\/ai-helps-doctors-diagnose-thecoronavirus\/. Accessed 3 Mar 2021"},{"issue":"17","key":"12450_CR9","doi-asserted-by":"publisher","first-page":"8039","DOI":"10.3390\/app11178039","volume":"11","author":"Y Akbari","year":"2021","unstructured":"Akbari Y, Hassen H, Al-Maadeed S, Zughaier SM (2021) COVID-19 lesion segmentation using lung CT scan images: comparative study based on active contour models. Appl Sci 11(17):8039","journal-title":"Appl Sci"},{"key":"12450_CR10","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.ijmedinf.2018.06.003","volume":"117","author":"MA Al-antari","year":"2018","unstructured":"Al-antari MA, Al-masni MA, Choi MT, Han SM, Kim TS (2018) A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification. Int J Med Inform 117:44\u201354","journal-title":"Int J Med Inform"},{"key":"12450_CR11","doi-asserted-by":"publisher","first-page":"85","DOI":"10.14740\/jmc3637","volume":"12","author":"K Alekseyev","year":"2021","unstructured":"Alekseyev K, Didenko L, Chaudhry B (2021) Rhinocerebral Mucormycosis and COVID-19 pneumonia. J Med Cases 12:85. https:\/\/doi.org\/10.14740\/jmc3637","journal-title":"J Med Cases"},{"key":"12450_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s15010-021-01670-1","volume":"49","author":"JA Al-Tawfiq","year":"2021","unstructured":"Al-Tawfiq JA, Alhumaid S, Alshukairi AN, Temsah MH, Barry M, Al Mutair A, \u2026 Dhama K (2021) COVID-19 and Mucormycosis superinfection: the perfect storm. Infection 49:1\u201321","journal-title":"Infection"},{"key":"12450_CR13","doi-asserted-by":"crossref","unstructured":"Andreu-Perez J, P\u00e9rez-Espinosa H, Timonet E, Kiani M, Giron-Perez MI, Benitez-Trinidad AB, .... Rivas F (2021) A generic deep learning based cough analysis system from clinically validated samples for point-of-need covid-19 test and severity levels. IEEE Trans Serv Comput","DOI":"10.31219\/osf.io\/tm2f7"},{"key":"12450_CR14","unstructured":"Asnaoui KE, Chawki Y, Idri A (2020) Automated methods for detection and classification pneumonia based on X-ray images using deep learning. arXiv preprint arXiv:2003.14363"},{"key":"12450_CR15","unstructured":"Aspergillosis (n.d.). [online]. Available: https:\/\/www.healthline.com\/health\/aspergillosis. Accessed 3 Mar 2021"},{"key":"12450_CR16","doi-asserted-by":"publisher","first-page":"138277","DOI":"10.1016\/j.scitotenv.2020.138277","volume":"725","author":"V Balachandar","year":"2020","unstructured":"Balachandar V, Kaavya J, Mahalaxmi I, Arul N, Vivekanandhan G, Bupesh G, Singaravelu G, Anila V, Dhivya V, Harsha G (2020a) COVID-19: a promising cure for the global panic. Sci Total Environ 725:138277. https:\/\/doi.org\/10.1016\/j.scitotenv.2020.138277","journal-title":"Sci Total Environ"},{"key":"12450_CR17","unstructured":"Barstugan M, Ozkaya U, Ozturk S (2020) Coronavirus (COVID-19) classification using CT images by machine learning methods. arXiv preprint arXiv:2003.09424"},{"key":"12450_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11042-021-10714-5","volume":"80","author":"A Bhargava","year":"2021","unstructured":"Bhargava A, Bansal A (2021) Novel coronavirus (COVID-19) diagnosis using computer vision and artificial intelligence techniques: a review. Multimed Tools Appl 80:1\u201316","journal-title":"Multimed Tools Appl"},{"key":"12450_CR19","unstructured":"Black fungus: Here is a list of states with highest number of Mucormycosis cases (n.d.). [online]. Available: https:\/\/www.hindustantimes.com\/india-news\/black-fungus-states-with-highest-number-of-Mucormycosis-cases-101621559394002.html. Accessed 3 Mar 2021"},{"issue":"14","key":"12450_CR20","doi-asserted-by":"publisher","first-page":"5596","DOI":"10.1109\/JSEN.2016.2567538","volume":"16","author":"R Blank","year":"2016","unstructured":"Blank R, Vinayaka PP, Tahir MW, Yong J, Vellekoop MJ, Lang W (2016) Comparison of several optical methods for an automated fungal spore sensor system concept. IEEE Sensors J 16(14):5596\u20135602","journal-title":"IEEE Sensors J"},{"key":"12450_CR21","doi-asserted-by":"crossref","unstructured":"Cao J, Jiang L, Hou J, Jiang L, Zhao R, Shi W ... Feng R (2021) Exploiting Deep Cross-Slice Features From CT Images For Multi-Class Pneumonia Classification. In; 2021 IEEE International Conference on Image Processing (ICIP) (pp. 205\u2013209). IEEE","DOI":"10.1109\/ICIP42928.2021.9506553"},{"key":"12450_CR22","doi-asserted-by":"publisher","first-page":"6480","DOI":"10.1109\/TII.2021.3057524","volume":"17","author":"A Castiglione","year":"2021","unstructured":"Castiglione A, Vijayakumar P, Nappi M, Sadiq S, Umer M (2021) COVID-19: automatic detection of the novel coronavirus disease from CT images using an optimized convolutional neural network. IEEE Trans Ind Inform 17:6480\u20136488","journal-title":"IEEE Trans Ind Inform"},{"key":"12450_CR23","doi-asserted-by":"publisher","first-page":"102800","DOI":"10.1016\/j.bspc.2021.102800","volume":"69","author":"S Chakraborty","year":"2021","unstructured":"Chakraborty S, Mali K (2021) A morphology-based radiological image segmentation approach for efficient screening of COVID-19. Biomed Signal Process Control 69:102800","journal-title":"Biomed Signal Process Control"},{"key":"12450_CR24","doi-asserted-by":"publisher","first-page":"6476","DOI":"10.1109\/TII.2021.3067670","volume":"17","author":"V Chang","year":"2021","unstructured":"Chang V, Abdel-Basset M, Iqbal R, Wills G (2021) IEEE transactions on industrial informatics EDITORIAL: advanced deep learning techniques for COVID-19. IEEE Trans Ind Inform 17:6476\u20136479","journal-title":"IEEE Trans Ind Inform"},{"key":"12450_CR25","doi-asserted-by":"crossref","unstructured":"Chen T, Chefd\u2019Hotel C (2014) Deep learning based automatic immune cell detection for immunohistochemistry images. In: International workshop on machine learning in medical imaging (pp. 17-24). Springer: Cham","DOI":"10.1007\/978-3-319-10581-9_3"},{"issue":"7","key":"12450_CR26","doi-asserted-by":"publisher","first-page":"1736","DOI":"10.1109\/TMI.2018.2890510","volume":"38","author":"G Chen","year":"2019","unstructured":"Chen G, Xiang D, Zhang B, Tian H, Yang X, Shi F, Zhu W, Tian B, Chen X (2019) Automatic pathological lung segmentation in low-dose CT image using eigenspace sparse shape composition. IEEE Trans Med Imaging 38(7):1736\u20131749","journal-title":"IEEE Trans Med Imaging"},{"key":"12450_CR27","first-page":"1","volume":"11","author":"R Chen","year":"2020","unstructured":"Chen R, Chen J, Meng QT (2020) Chest computed tomography images of early coronavirus disease (COVID-19). Can J Anesth\/J Can d'anesth\u00e9sie 11:1\u20132","journal-title":"Can J Anesth\/J Can d'anesth\u00e9sie"},{"issue":"1","key":"12450_CR28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-019-56847-4","volume":"10","author":"J Chen","year":"2020","unstructured":"Chen J, Wu L, Zhang J, Zhang L, Gong D, Zhao Y, Chen Q, Huang S, Yang M, Yang X, Hu S, Wang Y, Hu X, Zheng B, Zhang K, Wu H, Dong Z, Xu Y, Zhu Y, \u2026 Yu H (2020) Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography. Sci Rep 10(1):1\u201311","journal-title":"Sci Rep"},{"issue":"3","key":"12450_CR29","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1007\/BF00994018","volume":"20","author":"C Cortes","year":"1995","unstructured":"Cortes C, Vapnik V (1995) Support-vector networks. Mach Learn 20(3):273\u2013297","journal-title":"Mach Learn"},{"issue":"4","key":"12450_CR30","doi-asserted-by":"publisher","first-page":"491","DOI":"10.1109\/TNB.2014.2365851","volume":"14","author":"I Cosic","year":"2014","unstructured":"Cosic I, Lazar K, Cosic D (2014) Prediction of tubulin resonant frequencies using the resonant recognition model (RRM). IEEE Trans Nanobiosci 14(4):491\u2013496","journal-title":"IEEE Trans Nanobiosci"},{"key":"12450_CR31","unstructured":"COVID19 and Black Fungus: Everything you need to know about the rising Mucormycosis infections in India (n.d.). [online]. Available: https:\/\/en.gaonconnection.com\/covid19-black-fungus-Mucormycosis-infections-symptoms-treatement-icmr-india\/. Accessed 3 Mar 2021"},{"key":"12450_CR32","unstructured":"COVID-19 India FAQs: What is White Fungus, Who It Can Infect, How It Can Be Treated and More (n.d.). [online]. Available: https:\/\/weather.com\/en-IN\/india\/coronavirus\/news\/2021-05-21-covid-19-india-faqs-what-is-white-fungus-who-it-can-infect-how-it. Accessed 3 Mar 2021"},{"key":"12450_CR33","unstructured":"Covid-19: All you need to know about \u2018yellow fungus\u2019 (n.d.). [online]. Available: https:\/\/www.deccanherald.com\/national\/covid-19-all-you-need-to-know-about-yellow-fungus-989747.html. Accessed 3 Mar 2021"},{"key":"12450_CR34","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9780511801389","volume-title":"An introduction to support vector machines and other kernel-based learning methods","author":"N Cristianini","year":"2000","unstructured":"Cristianini N, Shawe-Taylor J (2000) An introduction to support vector machines and other kernel-based learning methods. Cambridge University Press"},{"key":"12450_CR35","first-page":"1","volume":"2020","author":"X Dai","year":"2020","unstructured":"Dai X, Cheng J, Gao Y, Guo S, Yang X, Xu X, Cen Y (2020) Deep belief network for feature extraction of urban artificial targets. Math Probl Eng 2020:1\u201313","journal-title":"Math Probl Eng"},{"key":"12450_CR36","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41598-021-83587-1","volume":"11","author":"KC Dantas","year":"2021","unstructured":"Dantas KC, Mauad T, de Andr\u00e9 CDS, Bierrenbach AL, Saldiva PHN (2021) A single-Centre, retrospective study of the incidence of invasive fungal infections during 85 years of autopsy service in Brazil. Sci Rep 11:1\u201310. https:\/\/doi.org\/10.1038\/s41598-021-83587-1","journal-title":"Sci Rep"},{"key":"12450_CR37","doi-asserted-by":"crossref","unstructured":"Dev C, Kumar K, Palathil A, Anjali T, Panicker V (2019) Machine learning based approach for detection of lung Cancer in DICOM CT image. In: Ambient communications and computer systems (pp. 161\u2013173). Springer: Singapore","DOI":"10.1007\/978-981-13-5934-7_15"},{"issue":"2","key":"12450_CR38","first-page":"1","volume":"5","author":"WF Elbossaty","year":"2021","unstructured":"Elbossaty WF (2021) The Black fungus is one of the bad Conse-quences of COVID 19. Clin Oncol 5(2):1\u20134","journal-title":"Clin Oncol"},{"issue":"2","key":"12450_CR39","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1109\/TPAMI.2013.122","volume":"36","author":"I Endres","year":"2013","unstructured":"Endres I, Hoiem D (2013) Category-independent object proposals with diverse ranking. IEEE Trans Pattern Anal Mach Intell 36(2):222\u2013234","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"12450_CR40","unstructured":"Explained: What Are Black, White And Yellow Fungal Infections, Why Do They Occur, And Precautions To Take (n.d.). [online]. Available: https:\/\/www.outlookindia.com\/website\/story\/india-news-explained-what-are-black-white-and-yellow-fungal-infections-why-do-they-occur-and-precautions-to-take\/383950. Accessed 3 Mar 2021"},{"key":"12450_CR41","unstructured":"First case of White Fungus found in Uttar Pradesh (n.d.). [online]. Available: https:\/\/www.dnaindia.com\/india\/report-first-case-of-white-fungus-found-in-uttar-pradesh-2891377. Accessed 3 Mar 2021"},{"key":"12450_CR42","unstructured":"Five Companies Using AI to Fight Coronavirus. (n.d.) [Online]. Available: https:\/\/spectrum.ieee.org\/thehuman-os\/artificial-intelligence\/medicalai\/companies-ai-coronavirus. Accessed 3 Mar 2021"},{"key":"12450_CR43","unstructured":"Ghoshal B, Tucker A (2020) Estimating uncertainty and interpretability in deep learning for coronavirus (COVID-19) detection. arXiv preprint arXiv:2003.10769"},{"key":"12450_CR44","unstructured":"Gozes O, Frid-Adar M, Greenspan H, Browning PD, Zhang H, Ji W, ... Siegel E (2020) Rapid ai development cycle for the coronavirus (covid-19) pandemic: Initial results for automated detection & patient monitoring using deep learning ct image analysis. arXiv preprint arXiv:2003.05037"},{"issue":"3","key":"12450_CR45","doi-asserted-by":"publisher","first-page":"133","DOI":"10.5530\/ijmedph.2021.3.24","volume":"11","author":"BM Gupta","year":"2021","unstructured":"Gupta BM, Mamdapur GM, Dayal D (2021) Black fungus (Mucormycosis) research in India during 1998-2021: A Scopus-based Scientometric analysis. Int J Med Public Health 11(3):133\u2013138","journal-title":"Int J Med Public Health"},{"key":"12450_CR46","doi-asserted-by":"crossref","unstructured":"Han C, Kitamura Y, Kudo A, Ichinose A, Rundo L, Furukawa Y ... Nakayama H (2019) Synthesizing diverse lung nodules wherever massively: 3D multi-conditional GAN-based CT image augmentation for object detection. In 2019 International Conference on 3D Vision (3DV) (pp. 729\u2013737). IEEE","DOI":"10.1109\/3DV.2019.00085"},{"key":"12450_CR47","doi-asserted-by":"publisher","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","volume":"6","author":"RM Haralick","year":"1973","unstructured":"Haralick RM, Shanmugam K, Dinstein IH (1973) Textural features for image classification. IEEE Trans Syst Man Cybern 6:610\u2013621","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"12450_CR48","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.media.2016.05.004","volume":"35","author":"M Havaei","year":"2017","unstructured":"Havaei M, Davy A, Warde-Farley D, Biard A, Courville A, Bengio Y, Pal C, Jodoin PM, Larochelle H (2017) Brain tumor segmentation with deep neural networks. Med Image Anal 35:18\u201331","journal-title":"Med Image Anal"},{"key":"12450_CR49","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 770-778)","DOI":"10.1109\/CVPR.2016.90"},{"key":"12450_CR50","doi-asserted-by":"crossref","unstructured":"He K, Gkioxari G, Doll\u00e1r P, Girshick R (2017) Mask r-cnn. In: Proceedings of the IEEE international conference on computer vision (pp. 2961-2969)","DOI":"10.1109\/ICCV.2017.322"},{"key":"12450_CR51","doi-asserted-by":"crossref","unstructured":"Imteaj A, Rahman T, Hossain MK, Alam MS, Rahat SA (2017) An IoT based fire alarming and authentication system for workhouse using raspberry pi 3. In: 2017 international conference on electrical, computer and communication engineering (ECCE) (pp. 899-904). IEEE","DOI":"10.1109\/ECACE.2017.7913031"},{"key":"12450_CR52","doi-asserted-by":"publisher","first-page":"114054","DOI":"10.1016\/j.eswa.2020.114054","volume":"164","author":"AM Ismael","year":"2021","unstructured":"Ismael AM, \u015eeng\u00fcr A (2021) Deep learning approaches for COVID-19 detection based on chest X-ray images. Expert Syst Appl 164:114054","journal-title":"Expert Syst Appl"},{"key":"12450_CR53","doi-asserted-by":"crossref","unstructured":"Jian Z, Wei Z (2010) Support vector machine for recognition of cucumber leaf diseases. In: 2010 2nd international conference on advanced computer control (Vol. 5, pp. 264-266). IEEE","DOI":"10.1109\/ICACC.2010.5487242"},{"key":"12450_CR54","doi-asserted-by":"crossref","unstructured":"Jin S, Wang B, Xu H, Luo C, Wei L, Zhao W, ... Xu W (2020) AI-assisted CT imaging analysis for COVID-19 screening: building and deploying a medical AI system in four weeks. MedRxiv","DOI":"10.1101\/2020.03.19.20039354"},{"issue":"3","key":"12450_CR55","doi-asserted-by":"publisher","first-page":"867","DOI":"10.1016\/j.bbe.2021.05.013","volume":"41","author":"SH Kassania","year":"2021","unstructured":"Kassania SH, Kassanib PH, Wesolowskic MJ, Schneidera KA, Detersa R (2021) Automatic detection of coronavirus disease (COVID-19) in X-ray and CT images: a machine learning based approach. Biocybern Biomed Eng 41(3):867\u2013879","journal-title":"Biocybern Biomed Eng"},{"issue":"5","key":"12450_CR56","doi-asserted-by":"publisher","first-page":"2010","DOI":"10.1128\/JCM.38.5.2010-2014.2000","volume":"38","author":"ZU Khan","year":"2000","unstructured":"Khan ZU, Kortom M, Marouf R, Chandy R, Rinaldi MG, Sutton DA (2000) Bilateral pulmonary aspergilloma caused by an atypical isolate of aspergillus terreus. J Clin Microbiol 38(5):2010\u20132014","journal-title":"J Clin Microbiol"},{"issue":"4","key":"12450_CR57","first-page":"1667","volume":"22","author":"W Kim","year":"2012","unstructured":"Kim W, Kim C (2012) Active contours driven by the salient edge energy model. IEEE Trans Image Process 22(4):1667\u20131673","journal-title":"IEEE Trans Image Process"},{"key":"12450_CR58","doi-asserted-by":"crossref","unstructured":"Koley S, Ghosal P (2017) An IoT enabled real-time communication and location tracking system for vehicular emergency. In: 2017 IEEE computer society annual symposium on VLSI (ISVLSI) (pp. 671-676). IEEE","DOI":"10.1109\/ISVLSI.2017.122"},{"issue":"06","key":"12450_CR59","doi-asserted-by":"publisher","first-page":"2150106","DOI":"10.1142\/S0218126621501061","volume":"30","author":"H Kumar","year":"2020","unstructured":"Kumar H, Tomar VK (2020) Design of low power with expanded noise margin subthreshold 12T SRAM cell for ultra-low power devices. J Circ Syst Comput 30(06):2150106. https:\/\/doi.org\/10.1142\/S0218126621501061","journal-title":"J Circ Syst Comput"},{"issue":"2","key":"12450_CR60","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1109\/TMI.2015.2477395","volume":"35","author":"JW Kuo","year":"2015","unstructured":"Kuo JW, Mamou J, Aristiz\u00e1bal O, Zhao X, Ketterling JA, Wang Y (2015) Nested graph cut for automatic segmentation of high-frequency ultrasound images of the mouse embryo. IEEE Trans Med Imaging 35(2):427\u2013441","journal-title":"IEEE Trans Med Imaging"},{"issue":"2","key":"12450_CR61","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1109\/TMI.2017.2769839","volume":"37","author":"N Lessmann","year":"2017","unstructured":"Lessmann N, van Ginneken B, Zreik M, de Jong PA, de Vos BD, Viergever MA, I\u0161gum I (2017) Automatic calcium scoring in low-dose chest CT using deep neural networks with dilated convolutions. IEEE Trans Med Imaging 37(2):615\u2013625","journal-title":"IEEE Trans Med Imaging"},{"key":"12450_CR62","doi-asserted-by":"publisher","first-page":"E65","DOI":"10.1148\/radiol.2020200905","volume":"296","author":"L Li","year":"2020","unstructured":"Li L, Qin L, Xu Z, Yin Y, Wang X, Kong B, Bai J, Lu Y, Fang Z, Song Q, Cao K, Liu D, Wang G, Xu Q, Fang X, Zhang S, Xia J, Xia J (2020) Artificial intelligence distinguishes COVID-19 from community acquired pneumonia on chest CT. Radiology 296:E65\u2013E71","journal-title":"Radiology"},{"key":"12450_CR63","doi-asserted-by":"publisher","first-page":"102600","DOI":"10.1016\/j.scs.2020.102600","volume":"65","author":"M Loey","year":"2021","unstructured":"Loey M, Manogaran G, Taha MHN, Khalifa NEM (2021) Fighting against COVID-19: A novel deep learning model based on YOLO-v2 with ResNet-50 for medical face mask detection. Sustain Cities Soc 65:102600","journal-title":"Sustain Cities Soc"},{"issue":"2","key":"12450_CR64","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","volume":"60","author":"DG Lowe","year":"2004","unstructured":"Lowe DG (2004) Distinctive image features from scale-invariant keypoints. Int J Comput Vis 60(2):91\u2013110","journal-title":"Int J Comput Vis"},{"key":"12450_CR65","doi-asserted-by":"publisher","first-page":"111643","DOI":"10.1016\/j.envres.2021.111643","volume":"111643","author":"I Mahalaxmi","year":"2021","unstructured":"Mahalaxmi I, Jayaramayya K, Venkatesan D, Subramaniam MD, Renu K, Vijayakumar P, Narayanasamy A, Gopalakrishnan AV, Kumar NS, Sivaprakash P, Sambasiva Rao KRS, Vellingiri B (2021) Mucormycosis: an opportunistic pathogen during COVID-19. Environ Res 111643:111643","journal-title":"Environ Res"},{"key":"12450_CR66","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1002\/jcp.29937","volume":"236","author":"I Mahalaxmi","year":"2021","unstructured":"Mahalaxmi I, Kaavya J, Mohana Devi S, Balachandar V (2021) COVID-19 and olfactory dysfunction: a possible associative approach towards neurodegenerative diseases. J Cell Physiol 236:763\u2013770. https:\/\/doi.org\/10.1002\/jcp.29937","journal-title":"J Cell Physiol"},{"key":"12450_CR67","doi-asserted-by":"publisher","first-page":"105957","DOI":"10.1016\/j.ijscr.2021.105957","volume":"82","author":"A Maini","year":"2021","unstructured":"Maini A, Tomar G, Khanna D, Kini Y, Mehta H, Bhagyasree V (2021) Sino-orbital Mucormycosis in a COVID-19 patient: a case report. Int J Surg Case Rep 82:105957. https:\/\/doi.org\/10.1016\/j.ijscr.2021.105957","journal-title":"Int J Surg Case Rep"},{"key":"12450_CR68","doi-asserted-by":"publisher","first-page":"106687","DOI":"10.1016\/j.measurement.2019.05.078","volume":"148","author":"AG Medeiros","year":"2019","unstructured":"Medeiros AG, Guimar\u00e3es MT, Peixoto SA, Santos LDO, da Silva Barros AC, Rebou\u00e7as EDS, de Albuquerque VHC, Rebou\u00e7as Filho PP (2019) A new fast morphological geodesic active contour method for lung CT image segmentation. Measurement 148:106687","journal-title":"Measurement"},{"key":"12450_CR69","unstructured":"Mucormycosis: The 'black fungus' maiming Covid patients in India (n.d.). [online]. Available: https:\/\/www.bbc.com\/news\/world-asia-india-57027829. Accessed 3 Mar 2021"},{"key":"12450_CR70","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10044-021-00984-y","volume":"24","author":"A Narin","year":"2021","unstructured":"Narin A, Kaya C, Pamuk Z (2021) Automatic detection of coronavirus disease (covid-19) using x-ray images and deep convolutional neural networks. Pattern Anal Applic 24:1\u201314","journal-title":"Pattern Anal Applic"},{"key":"12450_CR71","doi-asserted-by":"publisher","first-page":"178","DOI":"10.3389\/fnins.2013.00178","volume":"7","author":"P O'Connor","year":"2013","unstructured":"O'Connor P, Neil D, Liu SC, Delbruck T, Pfeiffer M (2013) Real-time classification and sensor fusion with a spiking deep belief network. Front Neurosci 7:178","journal-title":"Front Neurosci"},{"key":"12450_CR72","doi-asserted-by":"crossref","unstructured":"Pardeshi V, Sagar S, Murmurwar S, Hage P (2017). Health monitoring systems using IoT and raspberry pi\u2014a review. In: 2017 international conference on innovative mechanisms for industry applications (ICIMIA) (pp. 134-137). IEEE","DOI":"10.1109\/ICIMIA.2017.7975587"},{"issue":"3","key":"12450_CR73","doi-asserted-by":"publisher","first-page":"374","DOI":"10.1002\/ima.22340","volume":"29","author":"T Paulraj","year":"2019","unstructured":"Paulraj T, Chelliah KSV, Chinnasamy S (2019) Lung computed axial tomography image segmentation using possibilistic fuzzy C-means approach for computer aided diagnosis system. Int J Imaging Syst Technol 29(3):374\u2013381","journal-title":"Int J Imaging Syst Technol"},{"issue":"8","key":"12450_CR74","doi-asserted-by":"publisher","first-page":"616","DOI":"10.3390\/jof7080616","volume":"7","author":"H Prakash","year":"2021","unstructured":"Prakash H, Skiada A, Paul RA, Chakrabarti A, Rudramurthy SM (2021) Connecting the dots: interplay of pathogenic mechanisms between COVID-19 disease and Mucormycosis. J Fungi 7(8):616","journal-title":"J Fungi"},{"issue":"6","key":"12450_CR75","first-page":"321","volume":"6","author":"JD Pujari","year":"2013","unstructured":"Pujari JD, Yakkundimath R, Byadgi AS (2013) Classification of fungal disease symptoms affected on cereals using color texture features. Int J Signal Process Image Process Pattern Recog 6(6):321\u2013330","journal-title":"Int J Signal Process Image Process Pattern Recog"},{"key":"12450_CR76","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00405-021-06932-0","volume":"278","author":"AF Raza","year":"2021","unstructured":"Raza AF, Paudel DR, Prabhu P (2021) Black fungus and COVID-19: role of otorhinolaryngologists and audiologists. Eur Arch Otorhinolaryngol 278:1\u20132","journal-title":"Eur Arch Otorhinolaryngol"},{"issue":"2","key":"12450_CR77","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1109\/TMI.2013.2270114","volume":"33","author":"A Ribbens","year":"2013","unstructured":"Ribbens A, Hermans J, Maes F, Vandermeulen D, Suetens P (2013) Unsupervised segmentation, clustering, and groupwise registration of heterogeneous populations of brain MR images. IEEE Trans Med Imaging 33(2):201\u2013224","journal-title":"IEEE Trans Med Imaging"},{"key":"12450_CR78","doi-asserted-by":"publisher","first-page":"702","DOI":"10.1016\/j.measurement.2019.05.027","volume":"145","author":"PM Shakeel","year":"2019","unstructured":"Shakeel PM, Burhanuddin MA, Desa MI (2019) Lung cancer detection from CT image using improved profuse clustering and deep learning instantaneously trained neural networks. Measurement 145:702\u2013712","journal-title":"Measurement"},{"key":"12450_CR79","unstructured":"Shan F, Gao Y, Wang J, Shi W, Shi N, Han M ... Shi Y (2020) Lung infection quantification of COVID-19 in CT images with deep learning. arXiv preprint arXiv:2003.04655"},{"key":"12450_CR80","doi-asserted-by":"publisher","first-page":"2329","DOI":"10.2147\/IDR.S254478","volume":"13","author":"A Shariati","year":"2020","unstructured":"Shariati A, Moradabadi A, Chegini Z, Khoshbayan A, Didehdar M (2020) An overview of the management of the most important invasive fungal infections in patients with blood malignancies. Infect Drug Resist 13:2329\u20132354. https:\/\/doi.org\/10.2147\/IDR.S254478","journal-title":"Infect Drug Resist"},{"issue":"5","key":"12450_CR81","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1017\/S0022215121000992","volume":"135","author":"S Sharma","year":"2021","unstructured":"Sharma S, Grover M, Bhargava S, Samdani S, Kataria T (2021) Post coronavirus disease Mucormycosis: a deadly addition to the pandemic spectrum. J Laryngol Otol 135(5):442\u2013447","journal-title":"J Laryngol Otol"},{"issue":"8","key":"12450_CR82","doi-asserted-by":"publisher","first-page":"888","DOI":"10.1109\/34.868688","volume":"22","author":"J Shi","year":"2000","unstructured":"Shi J, Malik J (2000) Normalized cuts and image segmentation. IEEE Trans Pattern Anal Mach Intell 22(8):888\u2013905","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"12450_CR83","doi-asserted-by":"crossref","unstructured":"Shi F, Xia L, Shan F, Wu D, Wei Y, Yuan H ... Shen D (2020) Large-scale screening of covid-19 from community acquired pneumonia using infection size-aware classification. arXiv preprint arXiv:2003.09860","DOI":"10.1088\/1361-6560\/abe838"},{"key":"12450_CR84","doi-asserted-by":"publisher","first-page":"53040","DOI":"10.1109\/ACCESS.2019.2912200","volume":"7","author":"A Shrestha","year":"2019","unstructured":"Shrestha A, Mahmood A (2019) Review of deep learning algorithms and architectures. IEEE Access 7:53040\u201353065","journal-title":"IEEE Access"},{"key":"12450_CR85","unstructured":"Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. arXiv preprint arXiv:1409.1556"},{"key":"12450_CR86","doi-asserted-by":"crossref","unstructured":"Singh AK, Singh R, Joshi SR, Misra A (2021) Mucormycosis in COVID-19: a systematic review of cases reported worldwide and in India. Diabetes Metab Syndr Cli Res Rev","DOI":"10.1016\/j.dsx.2021.05.019"},{"key":"12450_CR87","volume-title":"Mucormycosis: the Black fungus hitting Covid-19 patients","author":"M Slavin","year":"2021","unstructured":"Slavin M, Thursky K (2021) Mucormycosis: the Black fungus hitting Covid-19 patients. BBC"},{"key":"12450_CR88","unstructured":"Song Y, Zhang L, Chen S, Ni D, Li B, Zhou Y ... Wang T (2014) A deep learning based framework for accurate segmentation of cervical cytoplasm and nuclei. In: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (pp. 2903\u20132906). IEEE"},{"key":"12450_CR89","doi-asserted-by":"publisher","first-page":"2775","DOI":"10.1109\/TCBB.2021.3065361","volume":"18","author":"Y Song","year":"2021","unstructured":"Song Y, Zheng S, Li L, Zhang X, Zhang X, Huang Z, Chen J, Wang R, Zhao H, Chong Y, Shen J, Zha Y, Yang Y (2021) Deep learning enables accurate diagnosis of novel coronavirus (COVID-19) with CT images. IEEE\/ACM Trans Comput Biol Bioinform 18:2775\u20132780","journal-title":"IEEE\/ACM Trans Comput Biol Bioinform"},{"key":"12450_CR90","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.compmedimag.2017.06.003","volume":"65","author":"P Swierczynski","year":"2018","unstructured":"Swierczynski P, Papie\u017c BW, Schnabel JA, Macdonald C (2018) A level-set approach to joint image segmentation and registration with application to CT lung imaging. Comput Med Imaging Graph 65:58\u201368","journal-title":"Comput Med Imaging Graph"},{"key":"12450_CR91","doi-asserted-by":"crossref","unstructured":"Szegedy C, Liu W, Jia Y, Sermanet P, Reed S, Anguelov D ... Rabinovich A (2015) Going deeper with convolutions. In: Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 1\u20139)","DOI":"10.1109\/CVPR.2015.7298594"},{"issue":"16","key":"12450_CR92","doi-asserted-by":"publisher","first-page":"5341","DOI":"10.1109\/JSEN.2017.2723052","volume":"17","author":"MW Tahir","year":"2017","unstructured":"Tahir MW, Zaidi NA, Blank R, Vinayaka PP, Vellekoop MJ, Lang W (2017) Fungus detection through optical sensor system using two different kinds of feature vectors for the classification. IEEE Sensors J 17(16):5341\u20135349","journal-title":"IEEE Sensors J"},{"key":"12450_CR93","doi-asserted-by":"crossref","unstructured":"Tan C, Sun F, Kong T, Zhang W, Yang C, Liu C (2018) A survey on deep transfer learning. In: International conference on artificial neural networks (pp. 270-279). Springer: Cham","DOI":"10.1007\/978-3-030-01424-7_27"},{"key":"12450_CR94","unstructured":"Tang Z, Zhao W, Xie X, Zhong Z, Shi F, Liu J, Shen D (2020) Severity assessment of coronavirus disease 2019 (COVID-19) using quantitative features from chest CT images. arXiv preprint arXiv:2003.11988"},{"key":"12450_CR95","doi-asserted-by":"publisher","first-page":"6539","DOI":"10.1109\/TII.2021.3057683","volume":"17","author":"S Tang","year":"2021","unstructured":"Tang S, Wang C, Nie J, Kumar N, Zhang Y, Xiong Z, Barnawi A (2021) EDL-COVID: ensemble deep learning for COVID-19 cases detection from chest X-ray images. IEEE Trans Ind Inform 17:6539\u20136549","journal-title":"IEEE Trans Ind Inform"},{"key":"12450_CR96","doi-asserted-by":"publisher","first-page":"2748","DOI":"10.26355\/eurrev_202103_25438","volume":"25","author":"M Vishnupriya","year":"2021","unstructured":"Vishnupriya M, Naveenkumar M, Manjima K, Sooryasree N, Saranya T, Ramya S, Winster SH, Paulpandi M, Balachandar V, Arul N (2021) Post-COVID pulmonary fibrosis: therapeutic efficacy using with mesenchymal stem cells\u2013how the lung heals. Eur Rev Med Pharmacol Sci 25:2748\u20132751. https:\/\/doi.org\/10.26355\/eurrev_202103_25438","journal-title":"Eur Rev Med Pharmacol Sci"},{"key":"12450_CR97","doi-asserted-by":"publisher","first-page":"135","DOI":"10.1016\/j.future.2020.02.054","volume":"108","author":"EK Wang","year":"2020","unstructured":"Wang EK, Chen CM, Hassan MM, Almogren A (2020) A deep learning based medical image segmentation technique in internet-of-medical-things domain. Futur Gener Comput Syst 108:135\u2013144","journal-title":"Futur Gener Comput Syst"},{"issue":"1","key":"12450_CR98","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-019-56847-4","volume":"10","author":"L Wang","year":"2020","unstructured":"Wang L, Lin ZQ, Wong A (2020) Covid-net: A tailored deep convolutional neural network design for detection of covid-19 cases from chest x-ray images. Sci Rep 10(1):1\u201312","journal-title":"Sci Rep"},{"key":"12450_CR99","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00330-021-07715-1","volume":"31","author":"S Wang","year":"2021","unstructured":"Wang S, Kang B, Ma J, Zeng X, Xiao M, Guo J, Cai M, Yang J, Li Y, Meng X, Xu B (2021) A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19). Eur Radiol 31:1\u20139","journal-title":"Eur Radiol"},{"issue":"3","key":"12450_CR100","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1080\/21681163.2016.1149104","volume":"6","author":"W Xie","year":"2018","unstructured":"Xie W, Noble JA, Zisserman A (2018) Microscopy cell counting and detection with fully convolutional regression networks. Comput Methods Biomech Biomed Eng Imaging Vis 6(3):283\u2013292","journal-title":"Comput Methods Biomech Biomed Eng Imaging Vis"},{"issue":"10","key":"12450_CR101","doi-asserted-by":"publisher","first-page":"1122","DOI":"10.1016\/j.eng.2020.04.010","volume":"6","author":"X Xu","year":"2020","unstructured":"Xu X, Jiang X, Ma C, Du P, Li X, Lv S, \u2026 Li L (2020) A deep learning system to screen novel coronavirus disease 2019 pneumonia. Engineering 6(10):1122\u20131129","journal-title":"Engineering"},{"key":"12450_CR102","doi-asserted-by":"publisher","first-page":"2808","DOI":"10.1109\/TMI.2021.3066161","volume":"40","author":"Q Yao","year":"2021","unstructured":"Yao Q, Xiao L, Liu P, Zhou SK (2021) Label-free segmentation of COVID-19 lesions in lung CT. IEEE Trans Med Imaging 40:2808\u20132819","journal-title":"IEEE Trans Med Imaging"},{"key":"12450_CR103","doi-asserted-by":"publisher","first-page":"23421","DOI":"10.1109\/ACCESS.2019.2899635","volume":"7","author":"C Ye","year":"2019","unstructured":"Ye C, Wang W, Zhang S, Wang K (2019) Multi-depth fusion network for whole-heart CT image segmentation. IEEE Access 7:23421\u201323429","journal-title":"IEEE Access"},{"key":"12450_CR104","unstructured":"Yellow fungus cases reported in UP: Know why it can prove more dangerous than black, white fungus (n.d.). [online]. Available:\u00a0https:\/\/timesofindia.indiatimes.com\/life-style\/health-fitness\/health-news\/yellow-fungus-cases-reported-in-up-know-why-it-can-prove-more-dangerous-than-black-fungus-white-fungus\/photostory\/82905030.cms. Accessed 3 Mar 2021"},{"issue":"2","key":"12450_CR105","doi-asserted-by":"publisher","first-page":"546","DOI":"10.1109\/TCYB.2015.2409119","volume":"46","author":"K Zhang","year":"2015","unstructured":"Zhang K, Zhang L, Lam KM, Zhang D (2015) A level set approach to image segmentation with intensity inhomogeneity. IEEE Trans Cybern 46(2):546\u2013557","journal-title":"IEEE Trans Cybern"},{"key":"12450_CR106","unstructured":"Zhang J, Xie Y, Li Y, Shen C, Xia Y (2020) Covid-19 screening on chest x-ray images using deep learning based anomaly detection. arXiv preprint arXiv:2003.12338"},{"key":"12450_CR107","doi-asserted-by":"crossref","unstructured":"Zheng C, Deng X, Fu Q, Zhou Q, Feng J, Ma H, ... Wang X (2020) Deep learning-based detection for COVID-19 from chest CT using weak label. MedRxiv","DOI":"10.1101\/2020.03.12.20027185"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-12450-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-022-12450-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-022-12450-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,9]],"date-time":"2025-04-09T11:29:09Z","timestamp":1744198149000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-022-12450-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,25]]},"references-count":107,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2022,4]]}},"alternative-id":["12450"],"URL":"https:\/\/doi.org\/10.1007\/s11042-022-12450-w","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2022,2,25]]},"assertion":[{"value":"12 June 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 September 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 January 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 February 2022","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Authors do not have any conflicts.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}