{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/malaria-detection-using-image-processing-and","title":"Malaria Detection Using Image Processing and Machine Learning","arxiv_id":"1801.10031","date":"2018-01-28","proceeding":null,"authors":["Suman Kunwar"],"abstract":"Malaria is mosquito-borne blood disease caused by parasites of the genus\nPlasmodium. Conventional diagnostic tool for malaria is the examination of\nstained blood cell of patient in microscope. The blood to be tested is placed\nin a slide and is observed under a microscope to count the number of infected\nRBC. An expert technician is involved in the examination of the slide with\nintense visual and mental concentration. This is tiresome and time consuming\nprocess.\n  In this paper, we construct a new mage processing system for detection and\nquantification of plasmodium parasites in blood smear slide, later we develop\nMachine Learning algorithm to learn, detect and determine the types of infected\ncells according to its features.","url_abs":"http://arxiv.org/abs/1801.10031v2","url_pdf":"http://arxiv.org/pdf/1801.10031v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"malaria-detection-using-image-processing-and","repo_url":"https://github.com/sumn2u/react-typescript-pdf-reader","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"diagnostic","task_name":"Diagnostic"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}