{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,19]],"date-time":"2026-06-19T07:15:54Z","timestamp":1781853354143,"version":"3.54.5"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2024,12,10]],"date-time":"2024-12-10T00:00:00Z","timestamp":1733788800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,12,10]],"date-time":"2024-12-10T00:00:00Z","timestamp":1733788800000},"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":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1007\/s00521-024-10810-1","type":"journal-article","created":{"date-parts":[[2024,12,10]],"date-time":"2024-12-10T18:54:30Z","timestamp":1733856870000},"page":"3047-3059","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Deep learning-based ovarian cyst classification and abnormality detection using convolutional neural networks"],"prefix":"10.1007","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3038-6488","authenticated-orcid":false,"given":"Munish","family":"Sood","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emjee","family":"Puthooran","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nishant","family":"Jain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,12,10]]},"reference":[{"key":"10810_CR1","doi-asserted-by":"crossref","unstructured":"Brown DL, Dudiak KM, Laing FC (2010) Adnexal Masses: US Characterization and Reporting. https:\/\/doi:10.1148:radiol.09090552","DOI":"10.1148\/radiol.09090552"},{"key":"10810_CR2","doi-asserted-by":"publisher","first-page":"328","DOI":"10.1016\/j.ejrad.2007.02.040","volume":"62","author":"XuY LiuJ","year":"2007","unstructured":"LiuJ XuY, Wang J (2007) Ultrasonography, computed tomography and magnetic resonance imaging for diagnosis of ovarian carcinoma. Eur J Radiol 62:328\u2013334. https:\/\/doi.org\/10.1016\/j.ejrad.2007.02.040","journal-title":"Eur J Radiol"},{"key":"10810_CR3","doi-asserted-by":"publisher","first-page":"438","DOI":"10.1002\/uog.2707","volume":"27","author":"L Valentin","year":"2006","unstructured":"Valentin L, Ameye L, Jurkovic D et al (2006) Which extra uterine pelvic masses are difficult to correctly classify as benign or malignant on the basis of ultrasound findings and is there a way of making a correct diagnosis? Ultrasound Obstet Gynecol 27:438\u2013444. https:\/\/doi.org\/10.1002\/uog.2707","journal-title":"Ultrasound Obstet Gynecol"},{"key":"10810_CR4","doi-asserted-by":"publisher","first-page":"384","DOI":"10.1097\/AOG.0b013e318195ad17","volume":"113","author":"P Geomini","year":"2009","unstructured":"Geomini P, Kruitwagen R, Bremer GL, Cnossen J, Mol BW (2009) The accuracy of risk scores in predicting ovarian malignancy: a systematic review. Obstet Gynecol 113:384\u2013394. https:\/\/doi.org\/10.1097\/AOG.0b013e318195ad17","journal-title":"Obstet Gynecol"},{"key":"10810_CR5","doi-asserted-by":"publisher","unstructured":"Sohail ASM, Bhattacharya P, Mudur SP, Krishnamurthy S, Gilbert L (2010) Content-based retrieval and classification of ultrasound medical images of ovarian cysts. In: Proc. IAPR Workshop Artif. Neural Netw. Pattern Recognit., pp 173\u2013184. https:\/\/doi.org\/10.1007\/978-3-642-12159-3_16","DOI":"10.1007\/978-3-642-12159-3_16"},{"key":"10810_CR6","doi-asserted-by":"publisher","unstructured":"Rihana S, Moussallem H, Skaf C, Yaacoub C (2013) Automated algorithm for ovarian cysts detection in ultrasonogram. In: Proc. 2nd Int.Conf. Adv. Biomed. Eng., pp 219\u2013222. https:\/\/doi.org\/10.1109\/ICABME.2013.6648887","DOI":"10.1109\/ICABME.2013.6648887"},{"key":"10810_CR7","doi-asserted-by":"publisher","unstructured":"Nabilah A, Sigit R, Harsono T, Anwar A (2020) Classification of ovarian cysts on ultrasound images using watershed segmentation and contour analysis. In: Proc. Int. Electron. Symp. (IES), pp 513\u2013519. https:\/\/doi.org\/10.1038\/s41598-024-69427-y","DOI":"10.1038\/s41598-024-69427-y"},{"key":"10810_CR8","doi-asserted-by":"publisher","unstructured":"Parekh AM, Shah NB (2017) Classification of ovarian cyst using soft computing technique. In: Proc. 8th Int. Conf. Comput., Commun. Netw. Technol. (ICCCNT), pp 1\u20135. https:\/\/doi.org\/10.1109\/ICCCNT.2017.8203965","DOI":"10.1109\/ICCCNT.2017.8203965"},{"issue":"1","key":"10810_CR9","doi-asserted-by":"publisher","first-page":"43","DOI":"10.2174\/1573394711666150827204521","volume":"12","author":"S Rajendran","year":"2016","unstructured":"Rajendran S, Sankareswaran UM (2016) A novel pigeon inspired optimization in ovarian cyst detection. Current Med Imag Rev 12(1):43\u201349. https:\/\/doi.org\/10.2174\/1573394711666150827204521","journal-title":"Current Med Imag Rev"},{"key":"10810_CR10","doi-asserted-by":"publisher","unstructured":"Akter L, Akhter N (2022) Ovarian cancer prediction from ovarian cysts based on TVUS using machine learning algorithms. In: Proc. Int. Conf. Big Data, IoT, Mach. Learn. Springer, Cham, pp 51\u201361. https:\/\/doi.org\/10.48550\/arXiv.2108.13387","DOI":"10.48550\/arXiv.2108.13387"},{"key":"10810_CR11","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/J.NEUNET.2014.09.003","volume":"61","author":"J Schmidhuber","year":"2015","unstructured":"Schmidhuber J (2015) Deep learning in neural networks: an overview. Neural Netw 61:85\u2013117. https:\/\/doi.org\/10.1016\/J.NEUNET.2014.09.003","journal-title":"Neural Netw"},{"key":"10810_CR12","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1038\/nature21056","volume":"542","author":"A Esteva","year":"2017","unstructured":"Esteva A et al (2017) Dermatologist-level classification of skin cancer with deep neural networks. Nat 542:115. https:\/\/doi.org\/10.1038\/nature21056","journal-title":"Nat"},{"key":"10810_CR13","doi-asserted-by":"publisher","first-page":"500","DOI":"10.1038\/s41568-018-0016-5","volume":"18","author":"A Hosny","year":"2018","unstructured":"Hosny A, Parmar C, Quackenbush J, Schwartz LH, Aerts HJ (2018) Artificial intelligence in radiology. Nat Rev Cancer 18:500. https:\/\/doi.org\/10.1038\/s41568-018-0016-5","journal-title":"Nat Rev Cancer"},{"key":"10810_CR14","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","volume":"42","author":"G Litjens","year":"2017","unstructured":"Litjens G et al (2017) A survey on deep learning in medical image analysis. Med Image Anal 42:60\u201388. https:\/\/doi.org\/10.1016\/j.media.2017.07.005","journal-title":"Med Image Anal"},{"key":"10810_CR15","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1409.1556","author":"K Simonyan","year":"2014","unstructured":"Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition. CoRR. https:\/\/doi.org\/10.48550\/arXiv.1409.1556. (abs\/1409.1556)","journal-title":"CoRR"},{"key":"10810_CR16","doi-asserted-by":"publisher","unstructured":"Huang G, Liu Z, Weinberger KQ (2016) Densely connected convolutional networks. CoRR abs\/1608.06993. https:\/\/doi.org\/10.48550\/arXiv.1608.06993","DOI":"10.48550\/arXiv.1608.06993"},{"key":"10810_CR17","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1007\/s11263-015-0816-y","volume":"115","author":"O Russakovsky","year":"2015","unstructured":"Russakovsky O et al (2015) ImageNet large scale visual recognition challenge. Int J Comput Vis (IJCV) 115:211\u2013252. https:\/\/doi.org\/10.1007\/s11263-015-0816-y","journal-title":"Int J Comput Vis (IJCV)"},{"key":"10810_CR18","doi-asserted-by":"publisher","DOI":"10.1002\/jor.24617","author":"A Borjali","year":"2020","unstructured":"Borjali A, Chen AF, Muratoglu OK, Morid MA, Varadarajan KM (2020) Detecting total hip replacement prosthesis design on plain radiographs using deep convolutional neural network. J Orthop Res. https:\/\/doi.org\/10.1002\/jor.24617","journal-title":"J Orthop Res"},{"key":"10810_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.cell.2018.02.010","author":"DS Kermany","year":"2018","unstructured":"Kermany DS, Goldbaum M, Cai W, Valentim CCS, Liang H, Baxter SL, McKeown A, Yang Ge, Fangbing XW, Yan JD, Prasadha MK, Pei J, Ting MYL, Zhu J, Li C, Hewett S, Dong J, Ziyar I, Shi A, Zhang R, Zheng L, Hou R, Shi W, Xin Fu, Duan Y, Huu VAN, Wen C, Zhang ED, Zhang CL, Li O, Wang X, Singer MA, Sun X, Jie Xu, Ali Tafreshi M, Lewis A, Xia H, Zhang K (2018) Identifying medical diagnoses and treatable diseases by image-based deep learning. Cell Resour. https:\/\/doi.org\/10.1016\/j.cell.2018.02.010","journal-title":"Cell Resour"},{"issue":"6","key":"10810_CR20","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1016\/S1701-2163(16)32460-4","volume":"29","author":"P Glanc","year":"2007","unstructured":"Glanc P, Brofman N, Salem S, Kornecki A, Abrams J, Farine D (2007) The prevalence of incidental simple ovarian cysts \u2265\u00a03\u00a0cm detected by transvaginal sonography in early pregnancy. J Obstet Gynaecol Canada 29(6):502\u2013506. https:\/\/doi.org\/10.1016\/S1701-2163(16)32460-4","journal-title":"J Obstet Gynaecol Canada"},{"issue":"2","key":"10810_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s42979-020-0109-6","volume":"1","author":"S Srivastava","year":"2020","unstructured":"Srivastava S, Kumar P, Chaudhry V, Singh A (2020) Detection of ovarian cyst in ultrasound images using fine-tuned VGG-16 deep learning network. Social Netw Comput Sci 1(2):1\u20138. https:\/\/doi.org\/10.1007\/s42979-020-0109-6","journal-title":"Social Netw Comput Sci"},{"key":"10810_CR22","doi-asserted-by":"publisher","first-page":"54310","DOI":"10.1109\/ACCESS.2021.3071301","volume":"9","author":"Y Wang","year":"2021","unstructured":"Wang Y, Ge X, Ma H, Qi S, Zhang G, Yao Y (2021) Deep learning in medical ultrasound image analysis: a review. IEEE Access 9:54310\u201354324. https:\/\/doi.org\/10.1109\/ACCESS.2021.3071301","journal-title":"IEEE Access"},{"issue":"2","key":"10810_CR23","doi-asserted-by":"publisher","first-page":"135","DOI":"10.11152\/mu-2746","volume":"23","author":"EC Constantinescu","year":"2021","unstructured":"Constantinescu EC, Udri\u015ftoiu A-L, Udri\u015ftoiu \u015eC, Iacob AV, Gruionu LG, Gruionu G, S\u0103ndulescu L, S\u0103ftoiu A (2021) Transfer learning with pre-trained deep convolutional neural networks for the automatic assessment of liver steatosis in ultrasound images. Med Ultrason 23(2):135\u2013139. https:\/\/doi.org\/10.11152\/mu-2746","journal-title":"Med Ultrason"},{"key":"10810_CR24","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1002\/uog.23530","volume":"57","author":"F Christiansen","year":"2021","unstructured":"Christiansen F, Epstein EL, Smedberg E, Kerlund MA, Smith K, Epstein E (2021) Ultrasound image analysis using deep neural networks for discriminating between benign and malignant ovarian tumors: comparison with expert subjective assessment. Ultrasound Obstet Gynecol 57:155\u2013163. https:\/\/doi.org\/10.1002\/uog.23530","journal-title":"Ultrasound Obstet Gynecol"},{"key":"10810_CR25","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1007\/s10916-019-1356-8","volume":"43","author":"L Zhang","year":"2019","unstructured":"Zhang L, Huang J, Liu L (2019) Improved deep learning network based in combination with cost-sensitive learning for early detection of ovarian cancer in color ultrasound detecting system. J Med Syst 43:251. https:\/\/doi.org\/10.1007\/s10916-019-1356-8","journal-title":"J Med Syst"},{"key":"10810_CR26","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/s42979-020-0109-6","volume":"1","author":"S Srivastava","year":"2020","unstructured":"Srivastava S, Kumar P, Chaudhry V, Singh A (2020) Detection of ovarian cyst in ultrasound images using finetuned VGG16 deep learning network. SN Comput Sci 1:81. https:\/\/doi.org\/10.1007\/s42979-020-0109-6","journal-title":"SN Comput Sci"},{"key":"10810_CR27","doi-asserted-by":"publisher","DOI":"10.26438\/ijcse\/v7i6.538542","author":"S Panda","year":"2019","unstructured":"Panda S, Panda C (2019) A review on image classification using bag of features approach. Int J Comput Sci Eng. https:\/\/doi.org\/10.26438\/ijcse\/v7i6.538542","journal-title":"Int J Comput Sci Eng"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10810-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-024-10810-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-024-10810-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,7]],"date-time":"2025-02-07T08:59:11Z","timestamp":1738918751000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-024-10810-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,10]]},"references-count":27,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["10810"],"URL":"https:\/\/doi.org\/10.1007\/s00521-024-10810-1","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,10]]},"assertion":[{"value":"3 June 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 November 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 December 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}