{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T15:18:13Z","timestamp":1771514293198,"version":"3.50.1"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319469751","type":"print"},{"value":"9783319469768","type":"electronic"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-46976-8_21","type":"book-chapter","created":{"date-parts":[[2016,9,25]],"date-time":"2016-09-25T23:43:16Z","timestamp":1474846996000},"page":"197-205","source":"Crossref","is-referenced-by-count":101,"title":["A Region Based Convolutional Network for Tumor Detection and Classification in Breast Mammography"],"prefix":"10.1007","author":[{"given":"Ayelet","family":"Akselrod-Ballin","sequence":"first","affiliation":[]},{"given":"Leonid","family":"Karlinsky","sequence":"additional","affiliation":[]},{"given":"Sharon","family":"Alpert","sequence":"additional","affiliation":[]},{"given":"Sharbell","family":"Hasoul","sequence":"additional","affiliation":[]},{"given":"Rami","family":"Ben-Ari","sequence":"additional","affiliation":[]},{"given":"Ella","family":"Barkan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,9,27]]},"reference":[{"issue":"2","key":"21_CR1","doi-asserted-by":"publisher","first-page":"71","DOI":"10.3322\/CA.2007.0010","volume":"58","author":"A Jemal","year":"2008","unstructured":"Jemal, A., Siegel, R., et al.: Cancer statistics, 2008. CA Cancer J. Clin. 58(2), 71\u201396 (2008)","journal-title":"CA Cancer J. Clin."},{"key":"21_CR2","unstructured":"American Cancer Society: Cancer facts and figures, Atlanta, GA (2015)"},{"key":"21_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"673","DOI":"10.1007\/978-3-642-13666-5_91","volume-title":"Digital Mammography","author":"F Narv\u00e1ez","year":"2010","unstructured":"Narv\u00e1ez, F., D\u00edaz, G., Romero, E.: Automatic BI-RADS description of mammographic masses. In: Mart\u00ed, J., Oliver, A., Freixenet, J., Mart\u00ed, R. (eds.) IWDM 2010. LNCS, vol. 6136, pp. 673\u2013681. Springer, Heidelberg (2010)"},{"key":"21_CR4","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, G.: Imagenet classification with deep convolutional neural networks. In: Proceedings of the (NIPS 2012), pp. 1097\u20131105 (2012)"},{"key":"21_CR5","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1146\/annurev-bioeng-071812-152416","volume":"15","author":"ML Giger","year":"2013","unstructured":"Giger, M.L., Karssemeijer, N., Schnabel, J.A.: Breast image analysis for risk assessment, detection, diagnosis, and treatment of cancer. Annu. Rev. Biomed. Eng. 15, 327\u2013357 (2013)","journal-title":"Annu. Rev. Biomed. Eng."},{"key":"21_CR6","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.media.2009.12.005","volume":"14","author":"A Oliver","year":"2010","unstructured":"Oliver, A., Freixenet, J., Marti, J., Perez, E., Pont, J., et al.: A review of automatic mass detection and segmentation in mammographic images. Med. Image Anal. 14, 87\u2013110 (2010)","journal-title":"Med. Image Anal."},{"key":"21_CR7","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1007\/978-3-319-24574-4_78","volume-title":"Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015","author":"G Carneiro","year":"2015","unstructured":"Carneiro, G., Nascimento, J., Bradley, A.P.: Unregistered multiview mammogram anaysis with pre-trained deep learning models. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 652\u2013660. Springer, Heidelberg (2015)"},{"key":"21_CR8","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1016\/j.cmpb.2015.12.014","volume":"127","author":"J Arevalo","year":"2016","unstructured":"Arevalo, J., Gonzales, F.A., Ramos-Poll\u00e1n, R., Oliveira, J.L., Lopez, M.A.G.: Representation learning for mammography mass lesion classification with convolutional neural networks. Comput. Methods Programs Biomed. 127, 248\u2013257 (2016)","journal-title":"Comput. Methods Programs Biomed."},{"key":"21_CR9","doi-asserted-by":"crossref","unstructured":"Dhungel, N., Carneiro, G., Bradley, A.: Automated mass detection from mammograms using deep learning and random forest. In: DICTA (2015)","DOI":"10.1109\/DICTA.2015.7371234"},{"key":"21_CR10","doi-asserted-by":"publisher","unstructured":"Girshick, R., Donahue, J., Darrell, T., Malik, J.: Rich feature hierarchies for accurate object detection and semantic segmentation. In: Computer Vision and Pattern Recognition (CVPR), pp. 580\u2013587 (2014)","DOI":"10.1109\/CVPR.2014.81"},{"key":"21_CR11","doi-asserted-by":"crossref","unstructured":"Girshickv, R.: Fast R-CNN. In: Proceedings of the IEEE International Conference on Computer Vision (ICCV), pp. 1440\u20131448 (2015)","DOI":"10.1109\/ICCV.2015.169"},{"key":"21_CR12","unstructured":"Ren, S., He, K., Girshick, R., Sun, J.: Faster R-CNN: towards real-time object detection with region proposal networks. In: NIPS (2015)"},{"key":"21_CR13","doi-asserted-by":"publisher","unstructured":"Ben-Ari, R., Zlotnick, A., Hashoul, S.: A weakly labeled approach for breast tissue segmentation and breast density estimation in digital mammography. In: ISBI (2016)","DOI":"10.1109\/ISBI.2016.7493368"},{"key":"21_CR14","unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. In: ICLR (2015)"},{"key":"21_CR15","unstructured":"Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., Darrell, T.: Caffe: convolutional architecture for fast feature embedding (2014). arXiv:1408.5093"},{"key":"21_CR16","unstructured":"Heath, M., Bowyer, K., et al.: The digital database for screening mammography. In: Proceedings of the 5th International Workshop on Digital Mammography, pp. 212\u2013218 (2000)"},{"issue":"2","key":"21_CR17","doi-asserted-by":"publisher","first-page":"236","DOI":"10.1016\/j.acra.2011.09.014","volume":"19","author":"IC Moreira","year":"2012","unstructured":"Moreira, I.C., Amaral, I., et al.: Inbreast: toward a full-field digital mammographic database. Acad. Radiol. 19(2), 236\u2013248 (2012)","journal-title":"Acad. Radiol."}],"container-title":["Lecture Notes in Computer Science","Deep Learning and Data Labeling for Medical Applications"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-46976-8_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T20:28:35Z","timestamp":1568406515000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-46976-8_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319469751","9783319469768"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-46976-8_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016]]}}}