{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T05:40:09Z","timestamp":1746769209374,"version":"3.40.5"},"publisher-location":"Cham","reference-count":38,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031882197","type":"print"},{"value":"9783031882203","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-88220-3_24","type":"book-chapter","created":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T05:06:55Z","timestamp":1746767215000},"page":"335-349","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DNA Fragmentation Estimation Using Light-Weight Deep Learning Model"],"prefix":"10.1007","author":[{"given":"Sudhanshu","family":"Rai","sequence":"first","affiliation":[]},{"given":"Samir","family":"Malakar","sequence":"additional","affiliation":[]},{"given":"Dilip K.","family":"Prasad","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,5,10]]},"reference":[{"key":"24_CR1","unstructured":"Agarwal, A., Allamaneni, S.: The effect of sperm DNA damage on assisted reproduction outcomes. a review. Minerva ginecologica 56(3), 235\u2013245 (2004)"},{"issue":"4","key":"24_CR2","doi-asserted-by":"publisher","first-page":"850","DOI":"10.1016\/j.fertnstert.2005.03.080","volume":"84","author":"A Agarwal","year":"2005","unstructured":"Agarwal, A., Allamaneni, S.S.: Sperm DNA damage assessment: a test whose time has come. Fertil. Steril. 84(4), 850\u2013853 (2005)","journal-title":"Fertil. Steril."},{"key":"24_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/s12610-016-0043-6","volume":"26","author":"PV Bach","year":"2016","unstructured":"Bach, P.V., Schlegel, P.N.: Sperm DNA damage and its role in IVF and ICSI. Basic Clin. Androl. 26, 1\u201310 (2016)","journal-title":"Basic Clin. Androl."},{"key":"24_CR4","doi-asserted-by":"crossref","unstructured":"Banerjee, N., Malakar, S., Gupta, D.K., Horsch, A., Prasad, D.K.: Guided u-net aided efficient image data storing with shape preservation. In: Asian Conference on Pattern Recognition, pp. 317\u2013330. Springer (2023)","DOI":"10.1007\/978-3-031-47634-1_24"},{"issue":"10","key":"24_CR5","doi-asserted-by":"publisher","first-page":"1979","DOI":"10.1364\/JOSAA.525577","volume":"41","author":"N Banerjee","year":"2024","unstructured":"Banerjee, N., Malakar, S., Horsch, A., Prasad, D.K.: Gunet++: guided-u-net-based compact image representation with an improved reconstruction mechanism. J. Opt. Soc. Am. A 41(10), 1979\u20131986 (2024)","journal-title":"J. Opt. Soc. Am. A"},{"key":"24_CR6","doi-asserted-by":"crossref","unstructured":"Butola, A., et al.: Deep learning architecture \u201clightoc\u201d for diagnostic decision support using optical coherence tomography images of biological samples. Biomed. Optics Express 11(9), 5017\u20135031 (2020)","DOI":"10.1364\/BOE.395487"},{"key":"24_CR7","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1007\/s00404-009-1140-y","volume":"281","author":"B Dari\u0161","year":"2010","unstructured":"Dari\u0161, B., Goropev\u0161ek, A., Hojnik, N., Vlaisavljevi\u0107, V.: Sperm morphological abnormalities as indicators of DNA fragmentation and fertilization in ICSI. Arch. Gynecol. Obstet. 281, 363\u2013367 (2010)","journal-title":"Arch. Gynecol. Obstet."},{"key":"24_CR8","doi-asserted-by":"publisher","first-page":"13367","DOI":"10.1007\/s00521-021-05964-1","volume":"33","author":"M Dey","year":"2021","unstructured":"Dey, M., et al.: A two-stage CNN-based hand-drawn electrical and electronic circuit component recognition system. Neural Comput. Appl. 33, 13367\u201313390 (2021)","journal-title":"Neural Comput. Appl."},{"key":"24_CR9","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1023\/A:1009844109023","volume":"22","author":"D Evenson","year":"2000","unstructured":"Evenson, D., Jost, L.: Sperm chromatin structure assay is useful for fertility assessment. Methods Cell Sci. 22, 169\u2013189 (2000)","journal-title":"Methods Cell Sci."},{"issue":"4","key":"24_CR10","doi-asserted-by":"publisher","first-page":"833","DOI":"10.1016\/j.fertnstert.2004.11.089","volume":"84","author":"JL Fern\u00e1ndez","year":"2005","unstructured":"Fern\u00e1ndez, J.L., et al.: Simple determination of human sperm DNA fragmentation with an improved sperm chromatin dispersion test. Fertil. Steril. 84(4), 833\u2013842 (2005)","journal-title":"Fertil. Steril."},{"key":"24_CR11","unstructured":"Frankle, J., Carbin, M.: The lottery ticket hypothesis: finding sparse, trainable neural networks. In: Proceedings of the The International Conference on Learning Representations (2019)"},{"issue":"4","key":"24_CR12","doi-asserted-by":"publisher","first-page":"981","DOI":"10.1007\/s10044-022-01083-2","volume":"25","author":"S Ganguly","year":"2022","unstructured":"Ganguly, S., Mohiuddin, S., Malakar, S., Cuevas, E., Sarkar, R.: Visual attention-based deepfake video forgery detection. Pattern Anal. Appl. 25(4), 981\u2013992 (2022)","journal-title":"Pattern Anal. Appl."},{"key":"24_CR13","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 770\u2013778 (2016)","DOI":"10.1109\/CVPR.2016.90"},{"key":"24_CR14","doi-asserted-by":"crossref","unstructured":"Howard, A., et\u00a0al.: Searching for mobilenetv3. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 1314\u20131324 (2019)","DOI":"10.1109\/ICCV.2019.00140"},{"key":"24_CR15","doi-asserted-by":"crossref","unstructured":"Huang, G., Liu, Z., Van Der\u00a0Maaten, L., Weinberger, K.Q.: Densely connected convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4700\u20134708 (2017)","DOI":"10.1109\/CVPR.2017.243"},{"key":"24_CR16","unstructured":"Iandola, F.N., Han, S., Moskewicz, M.W., Ashraf, K., Dally, W.J., Keutzer, K.: Squeezenet: alexnet-level accuracy with 50x fewer parameters and< 0.5 mb model size. arXiv preprint arXiv:1602.07360 (2016)"},{"issue":"1","key":"24_CR17","doi-asserted-by":"publisher","first-page":"14","DOI":"10.5653\/cerm.2019.46.1.14","volume":"46","author":"A Javed","year":"2019","unstructured":"Javed, A., Talkad, M.S., Ramaiah, M.K.: Evaluation of sperm DNA fragmentation using multiple methods: a comparison of their predictive power for male infertility. Clin. Exp. Reprod. Med. 46(1), 14 (2019)","journal-title":"Clin. Exp. Reprod. Med."},{"issue":"Suppl 10","key":"24_CR18","doi-asserted-by":"publisher","first-page":"S29","DOI":"10.1038\/nm-fertilityS29","volume":"8","author":"P Katz","year":"2002","unstructured":"Katz, P., Nachtigall, R., Showstack, J.: The economic impact of the assisted reproductive technologies. Nat. Med. 8(Suppl 10), S29\u2013S32 (2002)","journal-title":"Nat. Med."},{"issue":"1","key":"24_CR19","doi-asserted-by":"publisher","first-page":"16","DOI":"10.4103\/jhrs.jhrs_4_23","volume":"16","author":"RS Kumar","year":"2023","unstructured":"Kumar, R.S., Sharma, S., Halder, A., Gupta, V.: Deep learning-based robust automated system for predicting human sperm DNA fragmentation index. J. Human Reproductive Sci. 16(1), 16\u201321 (2023)","journal-title":"J. Human Reproductive Sci."},{"issue":"8","key":"24_CR20","doi-asserted-by":"publisher","first-page":"1581","DOI":"10.1111\/andr.13436","volume":"11","author":"S Kuroda","year":"2023","unstructured":"Kuroda, S., et al.: Novel sperm chromatin dispersion test with artificial intelligence-aided halo evaluation: a comparison study with existing modalities. Andrology 11(8), 1581\u20131592 (2023)","journal-title":"Andrology"},{"issue":"6","key":"24_CR21","doi-asserted-by":"publisher","first-page":"1564","DOI":"10.1016\/j.fertnstert.2013.08.017","volume":"100","author":"JJ Lim","year":"2013","unstructured":"Lim, J.J., et al.: DNA fragmentation of human sperm can be detected by ligation-mediated real-time polymerase chain reaction. Fertil. Steril. 100(6), 1564\u20131571 (2013)","journal-title":"Fertil. Steril."},{"key":"24_CR22","doi-asserted-by":"crossref","unstructured":"Malakar, S., Paul, S., Kundu, S., Bhowmik, S., Sarkar, R., Nasipuri, M.: Handwritten word recognition using lottery ticket hypothesis based pruned CNN model: a new benchmark on cmaterdb2. 1.2. Neural Comput. Appl. 32, 15209\u201315220 (2020)","DOI":"10.1007\/s00521-020-04872-0"},{"issue":"1","key":"24_CR23","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1038\/s42003-019-0491-6","volume":"2","author":"C McCallum","year":"2019","unstructured":"McCallum, C., et al.: Deep learning-based selection of human sperm with high DNA integrity. Commun. Biol. 2(1), 250 (2019)","journal-title":"Commun. Biol."},{"issue":"5","key":"24_CR24","doi-asserted-by":"publisher","first-page":"14011","DOI":"10.1007\/s11042-023-15408-8","volume":"83","author":"S Mondal","year":"2024","unstructured":"Mondal, S., De, P., Malakar, S., Sarkar, R.: Omrnet: a lightweight deep learning model for optical mark recognition. Multimed. Tools Appl. 83(5), 14011\u201314045 (2024)","journal-title":"Multimed. Tools Appl."},{"issue":"6","key":"24_CR25","doi-asserted-by":"publisher","first-page":"470","DOI":"10.1002\/cyto.a.24703","volume":"103","author":"L Noy","year":"2023","unstructured":"Noy, L., Barnea, I., Mirsky, S.K., Kamber, D., Levi, M., Shaked, N.T.: Sperm-cell DNA fragmentation prediction using label-free quantitative phase imaging and deep learning. Cytometry A 103(6), 470\u2013478 (2023)","journal-title":"Cytometry A"},{"issue":"3","key":"24_CR26","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1111\/j.2047-2927.2012.00041.x","volume":"1","author":"K Oleszczuk","year":"2013","unstructured":"Oleszczuk, K., Augustinsson, L., Bayat, N., Giwercman, A., Bungum, M.: Prevalence of high DNA fragmentation index in male partners of unexplained infertile couples. Andrology 1(3), 357\u2013360 (2013)","journal-title":"Andrology"},{"issue":"3","key":"24_CR27","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1093\/humrep\/der461","volume":"27","author":"J Ribas-Maynou","year":"2012","unstructured":"Ribas-Maynou, J., Garcia-Peiro, A., Abad, C., Amengual, M., Navarro, J., Benet, J.: Alkaline and neutral comet assay profiles of sperm DNA damage in clinical groups. Hum. Reprod. 27(3), 652\u2013658 (2012)","journal-title":"Hum. Reprod."},{"issue":"5","key":"24_CR28","doi-asserted-by":"publisher","first-page":"1124","DOI":"10.1016\/j.fertnstert.2012.07.1059","volume":"98","author":"V S\u00e1nchez","year":"2012","unstructured":"S\u00e1nchez, V., et al.: Oxidative DNA damage in human sperm can be detected by Raman microspectroscopy. Fertil. Steril. 98(5), 1124\u20131129 (2012)","journal-title":"Fertil. Steril."},{"key":"24_CR29","doi-asserted-by":"crossref","unstructured":"Sandler, M., Howard, A., Zhu, M., Zhmoginov, A., Chen, L.C.: Mobilenetv2: inverted residuals and linear bottlenecks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4510\u20134520 (2018)","DOI":"10.1109\/CVPR.2018.00474"},{"key":"24_CR30","doi-asserted-by":"crossref","unstructured":"Sapkota, N., Zhang, Y., Li, S., Liang, P., Zhao, Z., Chen, D.Z.: Shmc-net: a mask-guided feature fusion network for sperm head morphology classification. arXiv preprint arXiv:2402.03697 (2024)","DOI":"10.1109\/ISBI56570.2024.10635339"},{"issue":"12","key":"24_CR31","doi-asserted-by":"publisher","first-page":"1071","DOI":"10.1038\/s42256-021-00420-0","volume":"3","author":"AA Sekh","year":"2021","unstructured":"Sekh, A.A., et al.: Physics-based machine learning for subcellular segmentation in living cells. Nature Mach. Intell. 3(12), 1071\u20131080 (2021)","journal-title":"Nature Mach. Intell."},{"issue":"49","key":"24_CR32","doi-asserted-by":"publisher","DOI":"10.1088\/0957-4484\/22\/49\/494013","volume":"22","author":"L Shui","year":"2011","unstructured":"Shui, L., Bomer, J.G., Jin, M., Carlen, E.T., Van den Berg, A.: Microfluidic DNA fragmentation for on-chip genomic analysis. Nanotechnology 22(49), 494013 (2011)","journal-title":"Nanotechnology"},{"key":"24_CR33","doi-asserted-by":"crossref","unstructured":"Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., Wojna, Z.: Rethinking the inception architecture for computer vision. In: Proceedings of the IEEE Conference On Computer Vision and Pattern Recognition, pp. 2818\u20132826 (2016)","DOI":"10.1109\/CVPR.2016.308"},{"key":"24_CR34","unstructured":"Tan, M., Le, Q.: Efficientnet: Rethinking model scaling for convolutional neural networks. In: International Conference on Machine Learning, pp. 6105\u20136114. PMLR (2019)"},{"issue":"6","key":"24_CR35","doi-asserted-by":"publisher","first-page":"1502","DOI":"10.1016\/j.fertnstert.2014.10.021","volume":"102","author":"C Wang","year":"2014","unstructured":"Wang, C., Swerdloff, R.S.: Limitations of semen analysis as a test of male fertility and anticipated needs from newer tests. Fertil. Steril. 102(6), 1502\u20131507 (2014)","journal-title":"Fertil. Steril."},{"issue":"15","key":"24_CR36","doi-asserted-by":"publisher","first-page":"1900712","DOI":"10.1002\/advs.201900712","volume":"6","author":"Y Wang","year":"2019","unstructured":"Wang, Y., et al.: Prediction of DNA integrity from morphological parameters using a single-sperm DNA fragmentation index assay. Adv. Sci. 6(15), 1900712 (2019)","journal-title":"Adv. Sci."},{"key":"24_CR37","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1007\/s10815-010-9505-5","volume":"28","author":"M Wilding","year":"2011","unstructured":"Wilding, M., Coppola, G., Di Matteo, L., Palagiano, A., Fusco, E., Dale, B.: Intracytoplasmic injection of morphologically selected spermatozoa (IMSI) improves outcome after assisted reproduction by deselecting physiologically poor quality spermatozoa. J. Assist. Reprod. Genet. 28, 253\u2013262 (2011)","journal-title":"J. Assist. Reprod. Genet."},{"key":"24_CR38","doi-asserted-by":"crossref","unstructured":"Zandieh, Z., et al.: Comparing reactive oxygen species and dna fragmentation in semen samples of unexplained infertile and healthy fertile men. Irish J. Med. Sci. (1971-) 187, 657\u2013662 (2018)","DOI":"10.1007\/s11845-017-1708-7"}],"container-title":["Lecture Notes in Computer Science","Pattern Recognition. ICPR 2024 International Workshops and Challenges"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-88220-3_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,9]],"date-time":"2025-05-09T05:07:08Z","timestamp":1746767228000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-88220-3_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031882197","9783031882203"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-88220-3_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"10 May 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICPR","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Pattern Recognition","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Kolkata","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"India","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icpr2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/icpr2024.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}