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In this work, a computer-aided architecture for mass regions segmentation in DBT images using a dilated deep convolutional neural network (DCNN) is developed. First, to improve the low contrast of breast tumour candidate regions and depress the background tissue noise in the DBT image effectively, the constraint matrix is established after top-hat transformation and multiplied with the DBT image. Second, input image patches are generated, and the data augmentation technique is performed to create the training data set for training a dilated DCNN architecture. Then the mass regions in DBT images are preliminarily segmented; each pixel is divided into two different kinds of labels. Finally, the postprocessing procedure removes all false-positives regions with less than 50 voxels. The final segmentation results are obtained by smoothing the boundaries of the mass regions with a median filter. The testing accuracy (ACC), sensitivity (SEN), and the area under the receiver operating curve (AUC) are adopted as the evaluation metrics, and the ACC, SEN, as well as AUC are 86.3%, 85.6%, and 0.852 for segmenting the mass regions in DBT images on the entire data set, respectively. The experimental results indicate that our proposed approach achieves promising results compared with other classical CAD-based frameworks.<\/jats:p>","DOI":"10.1155\/2022\/9082694","type":"journal-article","created":{"date-parts":[[2022,2,2]],"date-time":"2022-02-02T16:35:51Z","timestamp":1643819751000},"page":"1-10","source":"Crossref","is-referenced-by-count":5,"title":["Automated Segmentation of Mass Regions in DBT Images Using a Dilated DCNN Approach"],"prefix":"10.1155","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3215-7726","authenticated-orcid":true,"given":"Jianming","family":"Ye","sequence":"first","affiliation":[{"name":"First Affiliated Hospital, Gannan Medical University, Ganzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1262-4887","authenticated-orcid":true,"given":"Weiji","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7328-7290","authenticated-orcid":true,"given":"Jianqing","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6727-2815","authenticated-orcid":true,"given":"Xiaomei","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3020-9051","authenticated-orcid":true,"given":"Liuyi","family":"Li","sequence":"additional","affiliation":[{"name":"School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0425-4166","authenticated-orcid":true,"given":"Chun","family":"Xie","sequence":"additional","affiliation":[{"name":"First Affiliated Hospital, Gannan Medical University, Ganzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5953-8150","authenticated-orcid":true,"given":"Gang","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Medical Engineering, The 73th Group Army Hospital of P.L.A, Xiamen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7162-0552","authenticated-orcid":true,"given":"Xiangcai","family":"Wang","sequence":"additional","affiliation":[{"name":"First Affiliated Hospital, Gannan Medical University, Ganzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1305-5057","authenticated-orcid":true,"given":"Xiaobo","family":"Lai","sequence":"additional","affiliation":[{"name":"School of Medical Technology and Information Engineering, Zhejiang Chinese Medical University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.21037\/tcr.2019.11.43"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1016\/j.crad.2019.09.145"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2019190951"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2019191337"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1007\/s11517-019-02072-0"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2019182627"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1016\/j.acra.2018.06.019"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1002\/mp.13113"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2018.09.002"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.2214\/ajr.17.18185"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-009-1616-y"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1186\/s13058-017-0845-2"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1118\/1.2968098"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1177\/153303460400300504"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1117\/12.709593"},{"key":"16","first-page":"7","article-title":"Fuzzy segmentation of masses in digital breast tomosynthesis images based on dynamic programming","volume":"12","author":"L. 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