{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,26]],"date-time":"2026-07-26T07:23:39Z","timestamp":1785050619507,"version":"3.55.0"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":["Med Biol Eng Comput"],"published-print":{"date-parts":[[2021,1]]},"DOI":"10.1007\/s11517-020-02291-w","type":"journal-article","created":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T11:02:22Z","timestamp":1609498942000},"page":"143-152","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Quantitative analysis of blood cells from microscopic images using convolutional neural network"],"prefix":"10.1007","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7674-4351","authenticated-orcid":false,"given":"Abel Worku","family":"Tessema","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed Aliy","family":"Mohammed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gizeaddis Lamesgin","family":"Simegn","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy Chung","family":"Kwa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,1,1]]},"reference":[{"key":"2291_CR1","unstructured":"Khan A (2017) An accurate and cost effective approach to blood cell count, no. January, pp. 17\u201324"},{"key":"2291_CR2","doi-asserted-by":"crossref","unstructured":"Moravapalle UP, Deshpande A, Kapoor A, Ramjee R, Ravi P (2017) Blood count on a smartphone microscope. Work Mob Comput Syst Appl:37\u201342","DOI":"10.1145\/3032970.3032986"},{"issue":"1","key":"2291_CR3","first-page":"18","volume":"50","author":"S Khan","year":"2012","unstructured":"Khan S, Khan A, Saleh Khattak F, Naseem A (2012) An accurate and cost effective approach to blood cell count. Int J Comput Appl 50(1):18\u201324","journal-title":"Int J Comput Appl"},{"issue":"10","key":"2291_CR4","doi-asserted-by":"publisher","first-page":"4466","DOI":"10.1364\/BOE.8.004466","volume":"8","author":"F Yi","year":"2017","unstructured":"Yi F, Moon I, Javidi B (2017) Automated red blood cells extraction from holographic images using fully convolutional neural networks. Biomed Opt Express 8(10):4466","journal-title":"Biomed Opt Express"},{"key":"2291_CR5","doi-asserted-by":"crossref","unstructured":"Elmazi D, Cuka M, Ikeda M, Matsuo K, Barolli L (2019) Application of fuzzy logic for selection of actor nodes in wsans \u2014implementation of two fuzzy-based systems and a testbed. Sensors (Switzerland) 19(24)","DOI":"10.3390\/s19245573"},{"issue":"12","key":"2291_CR6","doi-asserted-by":"publisher","first-page":"2757","DOI":"10.1007\/s11517-019-02060-4","volume":"57","author":"ME Bayrakdar","year":"2019","unstructured":"Bayrakdar ME (2019) Priority based health data monitoring with IEEE 802.11af technology in wireless medical sensor networks. Med Biol Eng Comput 57(12):2757\u20132769","journal-title":"Med Biol Eng Comput"},{"issue":"7","key":"2291_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/s17071602","volume":"17","author":"Y Hao","year":"2017","unstructured":"Hao Y, Peng L, Lu H, Hassan MM, Alamri A (2017) Energy harvesting based body area networks for smart health. Sensors (Switzerland) 17(7):1\u201310","journal-title":"Sensors (Switzerland)"},{"issue":"5","key":"2291_CR8","first-page":"2948","volume":"3","author":"M Thejashwini","year":"2015","unstructured":"Thejashwini M, Padma MC (2015) Counting of RBC\u2019s and WBC\u2019s using image processing technique. Int J Recent Innov Trends Comput Commun 3(5):2948\u20132953","journal-title":"Int J Recent Innov Trends Comput Commun"},{"issue":"1","key":"2291_CR9","first-page":"69","volume":"77","author":"S Azwai","year":"2007","unstructured":"Azwai S, Abdouslam O (2007) Morphological characteristics of blood cells in clinically normal adult llamas (Lama glama). Vet 77(1):69\u201379","journal-title":"Vet"},{"key":"2291_CR10","doi-asserted-by":"crossref","unstructured":"Othman MZ, Mohammed TS, Ali AB (2017) Neural network classification of white blood cell using microscopic images, IJACSA. Int J Adv Comput Sci Appl 8(5)","DOI":"10.14569\/IJACSA.2017.080513"},{"key":"2291_CR11","unstructured":"Shahin AI, Guo Y, Amin KM, Sharawi AA (2017) White blood cells identification system based on convolutional deep neural learning networks. Comput Methods Prog Biomed"},{"key":"2291_CR12","unstructured":"Paxton S, Peckham M, Adele K, Paxton S, Adele K, and Peckham M (2003) The leeds histology guide"},{"issue":"1","key":"2291_CR13","doi-asserted-by":"publisher","first-page":"13","DOI":"10.4103\/2153-3539.93895","volume":"3","author":"N Ramesh","year":"2012","unstructured":"Ramesh N, Dangott B, Salama ME, Tasdizen T (2012) Isolation and two-step classification of normal white blood cells in peripheral blood smears. J Pathol Inform 3(1):13","journal-title":"J Pathol Inform"},{"key":"2291_CR14","unstructured":"Veluchamy M, Perumal K, Ponuchamy T (2012) Feature extraction and classification of blood cells using artificial neural network. Am J Appl Sci"},{"key":"2291_CR15","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1016\/j.media.2016.06.037","volume":"33","author":"A Madabhushi","year":"2016","unstructured":"Madabhushi A, Lee G (2016) Image analysis and machine learning in digital pathology: challenges and opportunities. Med Image Anal 33:170\u2013175","journal-title":"Med Image Anal"},{"key":"2291_CR16","unstructured":"Aswathy MA and Jagannath M (2016) Detection of breast cancer on digital histopathology images: present status and future possibilities, Informatics Med. Unlocked, vol. 8, no. November 2016, pp. 74\u201379"},{"key":"2291_CR17","unstructured":"Parthasarathy D (2017) A brief history of CNNs in image segmentation: from R-CNN to mask R-CNN, Medium. [Online]. Available: https:\/\/blog.athelas.com\/a-brief-history-of-cnns-in-image-segmentation-from-r-cnn-to-mask-r-cnn-34ea83205de4. [Accessed: 05-Dec-2018]"},{"key":"2291_CR18","doi-asserted-by":"crossref","unstructured":"Delforouzi A, Pamarthi B, Grzegorzek M (2018) Training-based methods for comparison of object detection methods for visual object tracking. Sensors (Basel) 18(11)","DOI":"10.3390\/s18113994"},{"key":"2291_CR19","unstructured":"Hui J (2018) Object detection: speed and accuracy comparison (Faster R-CNN, R-FCN, SSD, FPN, RetinaNet and\u2026. [Online]. Available: https:\/\/medium.com\/@jonathan_hui\/object-detection-speed-and-accuracy-comparison-faster-r-cnn-r-fcn-ssd-and-yolo-5425656ae359. [Accessed: 11-Dec-2018]"},{"key":"2291_CR20","unstructured":"Jordan Jeremy (2018) An overview of object detection: one-stage methods. [Online]. Available: https:\/\/www.jeremyjordan.me\/object-detection-one-stage\/. [Accessed: 19-Aug-2019]"},{"key":"2291_CR21","unstructured":"Redmon J and Farhadi A (2018) YOLO: real-time object detection, 2018. [Online]. Available: https:\/\/pjreddie.com\/darknet\/yolo\/. [Accessed: 05-Dec-2018]"},{"key":"2291_CR22","unstructured":"Gautam A and Bhadauria H (2014) Classification of white blood cells based on morphological features, in 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 2363\u20132368"},{"issue":"58","key":"2291_CR23","first-page":"2278","volume":"5","author":"MA Rejula","year":"2016","unstructured":"Rejula MA, Kumar MKJ (2016) An efficient approach of segmentation on white blood cells using morphological operators and 2D-discrete wavelet transform with anfis classification. Int J Emerg Res Manag Technol 5(58):2278\u20139359","journal-title":"Int J Emerg Res Manag Technol"},{"key":"2291_CR24","doi-asserted-by":"crossref","unstructured":"Segui S, Pujol O, and Vitria J (2015) Learning to count with deep object features. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. Work. vol. 2015-Octob, pp. 90\u201396","DOI":"10.1109\/CVPRW.2015.7301276"},{"key":"2291_CR25","doi-asserted-by":"crossref","unstructured":"Cohen JP, Boucher G, Glastonbury CA, Lo HZ, Bengio Y (2017) Count-ception: counting by fully convolutional redundant counting. Comput Vis Pattern Recog","DOI":"10.1109\/ICCVW.2017.9"},{"key":"2291_CR26","doi-asserted-by":"crossref","unstructured":"Xie Y, Xing F, Kong X, Su H, and Yang L Beyond classification: structured regression for robust cell detection using convolutional neural network, in Medical Image Computing and Computer-Assisted Intervention \u2013 MICCAI 2015. MICCAI 2015. Lecture Notes in Computer Science, vol 9351, 2015, pp. 358\u2013365","DOI":"10.1007\/978-3-319-24574-4_43"},{"issue":"3","key":"2291_CR27","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"},{"key":"2291_CR28","unstructured":"Hern\u00e1ndez CX, Sultan MM, Pande VS (2018) Using deep learning for segmentation and counting within microscopy data. Comput Vis Pattern Recog"},{"key":"2291_CR29","unstructured":"Cai F and Verbeek FJ (2015) Dam-based rolling ball with fuzzy-rough constraints, a new background subtraction algorithm for image analysis in microscopy, 5th Int. Conf. Image Process. Theory, Tools Appl. 2015, IPTA 2015, pp. 298\u2013303"},{"key":"2291_CR30","unstructured":"Herrera-Navarro AM, Jim\u00e9nez Hern\u00e1ndez H, Peregrina-Barreto H, Manr\u00edquez-Guerrero F, and Terol-Villalobos IR (2013) A new measure of circularity based on distribution of the radius, vol. 17, no. 4, pp. 515\u2013526"},{"key":"2291_CR31","doi-asserted-by":"crossref","unstructured":"Redmon J, Farhadi A (2016) YOLO9000: better, faster, stronger. Comput Vis Pattern Recog","DOI":"10.1109\/CVPR.2017.690"},{"issue":"24","key":"2291_CR32","doi-asserted-by":"publisher","first-page":"2829","DOI":"10.1161\/CIRCULATIONAHA.110.985564","volume":"123","author":"T Palmerini","year":"2011","unstructured":"Palmerini T, Mehran R, Dangas G, Nikolsky E, Witzenbichler B, Guagliumi G, Dudek D, Genereux P, Caixeta A, Rabbani LR, Weisz G, Parise H, Fahy M, Xu K, Brodie B, Lansky A, Stone GW (2011) Impact of leukocyte count on mortality and bleeding in patients with myocardial infarction undergoing primary percutaneous coronary interventions: analysis from the harmonizing outcome with revascularization and stent in acute myocardial infarction trial. Circulation 123(24):2829\u20132837","journal-title":"Circulation"},{"key":"2291_CR33","doi-asserted-by":"publisher","first-page":"979302","DOI":"10.1155\/2014\/979302","volume":"2014","author":"YM Alomari","year":"2014","unstructured":"Alomari YM, Sheikh Abdullah SNH, Zaharatul Azma R, Omar K (2014) Automatic detection and quantification of WBCs and RBCs using iterative structured circle detection algorithm. Comput Math Methods Med 2014:979302","journal-title":"Comput Math Methods Med"},{"issue":"6","key":"2291_CR34","doi-asserted-by":"publisher","first-page":"503","DOI":"10.3343\/alm.2018.38.6.503","volume":"38","author":"EH Nah","year":"2018","unstructured":"Nah EH, Kim S, Cho S, Cho HI (2018) Complete blood count reference intervals and patterns of changes across pediatric, adult, and geriatric ages in Korea. Ann Lab Med 38(6):503\u2013511","journal-title":"Ann Lab Med"},{"key":"2291_CR35","doi-asserted-by":"publisher","first-page":"838","DOI":"10.1136\/jcp.2005.033787","volume":"60","author":"W Van Der Meer","year":"2007","unstructured":"Van Der Meer W, Van Gelder W, De Keijzer R, Willems H (2007) The divergent morphological classification of variant lymphocytes in blood smears. J Clin Pathol 60:838\u2013839","journal-title":"J Clin Pathol"}],"container-title":["Medical & Biological Engineering & Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-020-02291-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11517-020-02291-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11517-020-02291-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,1,17]],"date-time":"2021-01-17T22:03:37Z","timestamp":1610921017000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11517-020-02291-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":35,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["2291"],"URL":"https:\/\/doi.org\/10.1007\/s11517-020-02291-w","relation":{},"ISSN":["0140-0118","1741-0444"],"issn-type":[{"value":"0140-0118","type":"print"},{"value":"1741-0444","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"21 April 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 November 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 January 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}