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Also, prevention of this cancer can help to decrease the high cost of medical caring for breast cancer patients. In recent years, the computer\u2010aided technique is an important active field for automatic cancer detection. In this study, an automatic breast tumor diagnosis system is introduced. An improved Deer Hunting Optimization Algorithm (DHOA) is used as the optimization algorithm. The presented method utilized a hybrid feature\u2010based technique and a new optimized convolutional neural network (CNN). Simulations are applied to the DCE\u2010MRI dataset based on some performance indexes. The novel contribution of this paper is to apply the preprocessing stage to simplifying the classification. Besides, we used a new metaheuristic algorithm. Also, the feature extraction by Haralick texture and local binary pattern (LBP) is recommended. Due to the obtained results, the accuracy of this method is 98.89%, which represents the high potential and efficiency of this method.<\/jats:p>","DOI":"10.1155\/2021\/5396327","type":"journal-article","created":{"date-parts":[[2021,7,17]],"date-time":"2021-07-17T01:05:09Z","timestamp":1626483909000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Automatic Breast Tumor Diagnosis in MRI Based on a Hybrid CNN and Feature\u2010Based Method Using Improved Deer Hunting Optimization Algorithm"],"prefix":"10.1155","volume":"2021","author":[{"given":"Weitao","family":"Ha","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3530-777X","authenticated-orcid":false,"given":"Zahra","family":"Vahedi","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,7,16]]},"reference":[{"key":"e_1_2_11_1_2","doi-asserted-by":"publisher","DOI":"10.3322\/caac.21660"},{"key":"e_1_2_11_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-67441-4"},{"key":"e_1_2_11_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/access.2020.3007336"},{"key":"e_1_2_11_4_2","doi-asserted-by":"crossref","unstructured":"IbraheemA. M. RahoumaK. H. andHamedH. F. Automatic MRI breast tumor detection using discrete wavelet transform and support vector machines Proceedings of 2019 Novel Intelligent and Leading Emerging Sciences Conference (NILES) November 2019 Cario Egypt IEEE https:\/\/doi.org\/10.1109\/niles.2019.8909345.","DOI":"10.1109\/NILES.2019.8909345"},{"key":"e_1_2_11_5_2","doi-asserted-by":"publisher","DOI":"10.4018\/IJSIR.2020070101"},{"key":"e_1_2_11_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.physa.2019.123592"},{"key":"e_1_2_11_7_2","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/5528622"},{"key":"e_1_2_11_8_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.saa.2021.119732"},{"key":"e_1_2_11_9_2","doi-asserted-by":"publisher","DOI":"10.1080\/00051144.2020.1785784"},{"key":"e_1_2_11_10_2","doi-asserted-by":"crossref","unstructured":"HeidariM. An optimal machine learning model for breast lesion classification based on random projection algorithm for feature optimization Proceedings of Medical Imaging 2021: Imaging Informatics for Healthcare Research and Applications February 2021 San Deigo CF USA International Society for Optics and Photonics https:\/\/doi.org\/10.1117\/12.2580944.","DOI":"10.1117\/12.2580944"},{"key":"e_1_2_11_11_2","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1755\/1\/012037"},{"key":"e_1_2_11_12_2","doi-asserted-by":"crossref","unstructured":"ParvathavarthiniS.andDeepaD. A hybrid artificial neural network classifier based on feature selection using binary dragonfly optimization for breast cancer detection Proceedings of IOP Conference Series: Materials Science and Engineering April 2021 Bandung Indonesia IOP Publishing https:\/\/doi.org\/10.1088\/1757-899x\/1055\/1\/012107.","DOI":"10.1088\/1757-899X\/1055\/1\/012107"},{"key":"e_1_2_11_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/access.2021.3067597"},{"key":"e_1_2_11_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.egyr.2020.06.011"},{"key":"e_1_2_11_15_2","doi-asserted-by":"publisher","DOI":"10.1007\/s12065-021-00615-9"},{"key":"e_1_2_11_16_2","doi-asserted-by":"publisher","DOI":"10.2316\/j.2020.203-0189"},{"key":"e_1_2_11_17_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-56689-0_8"},{"key":"e_1_2_11_18_2","first-page":"187","volume-title":"Metaheuristics and Optimization in Computer and Electrical Engineering","author":"Navid R.","year":"2021"},{"key":"e_1_2_11_19_2","doi-asserted-by":"publisher","DOI":"10.1007\/s13246-021-00977-5"},{"key":"e_1_2_11_20_2","article-title":"A hybrid gene selection strategy based on fisher and ant colony optimization algorithm for breast cancer classification","volume":"17","author":"Hamim M.","year":"2021","journal-title":"International Journal of Online and Biomedical Engineering"},{"key":"e_1_2_11_21_2","doi-asserted-by":"publisher","DOI":"10.1142\/s219688882150007x"},{"key":"e_1_2_11_22_2","doi-asserted-by":"publisher","DOI":"10.32598\/jams.23.2.4672.1"},{"key":"e_1_2_11_23_2","first-page":"169","volume-title":"Metaheuristics and Optimization in Computer and Electrical Engineering","author":"Navid R.","year":"2021"},{"key":"e_1_2_11_24_2","doi-asserted-by":"publisher","DOI":"10.33258\/birex.v3i3"},{"key":"e_1_2_11_25_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.04.053"},{"key":"e_1_2_11_26_2","doi-asserted-by":"publisher","DOI":"10.1080\/21642583.2019.1681033"},{"key":"e_1_2_11_27_2","first-page":"36","article-title":"An image watermarking approach to combat geometric attacks using hybrid DWT, DCT and SVD Method","volume":"7","author":"Vahedi Z.","year":"2019","journal-title":"World Essays Journal"},{"key":"e_1_2_11_28_2","doi-asserted-by":"publisher","DOI":"10.1117\/12.2582753"}],"container-title":["Computational Intelligence and Neuroscience"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2021\/5396327.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cin\/2021\/5396327.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/2021\/5396327","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T11:13:10Z","timestamp":1722942790000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/2021\/5396327"}},"subtitle":[],"editor":[{"given":"Navid","family":"Razmjooy","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2021,1]]},"references-count":28,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2021,1]]}},"alternative-id":["10.1155\/2021\/5396327"],"URL":"https:\/\/doi.org\/10.1155\/2021\/5396327","archive":["Portico"],"relation":{},"ISSN":["1687-5265","1687-5273"],"issn-type":[{"value":"1687-5265","type":"print"},{"value":"1687-5273","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,1]]},"assertion":[{"value":"2021-05-15","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-07-06","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2021-07-16","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"5396327"}}