{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:40:45Z","timestamp":1753882845995,"version":"3.41.2"},"reference-count":17,"publisher":"World Scientific Pub Co Pte Ltd","issue":"04","funder":[{"name":"the team for science & technology and local development service of nantong institute of technology","award":["KJCXTD312"],"award-info":[{"award-number":["KJCXTD312"]}]},{"name":"the science and technology planning project of nantong city under grant","award":["JC2021214"],"award-info":[{"award-number":["JC2021214"]}]},{"name":"the science and technology planning project of nantong city","award":["JCZ20172"],"award-info":[{"award-number":["JCZ20172"]}]},{"name":"the science and technology planning project of nantong city","award":["JCZ20151"],"award-info":[{"award-number":["JCZ20151"]}]},{"name":"the science and technology planning project of nantong city","award":["JCZ20148"],"award-info":[{"award-number":["JCZ20148"]}]},{"name":"the science and technology planning project of nantong city","award":["JC2021198"],"award-info":[{"award-number":["JC2021198"]}]},{"name":"the key projects of innovation and entrepreneurship training program for college students in jiangsu province in 2021","award":["202112056003Z"],"award-info":[{"award-number":["202112056003Z"]}]},{"name":"the innovation and entrepreneurship training program of nantong institute of technology in 2021","award":["XDC2021036"],"award-info":[{"award-number":["XDC2021036"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2022,3,30]]},"abstract":"<jats:p> Automatic and accurate segmentation of tumor area from rectal CT image plays an extremely key role in the treatment and diagnosis of rectal cancer. This paper proposes the MR-U-Net network model. The improvement is that a pair of encoder and decoder is added longitudinally to the U-shaped structure, which is the network structure of the fifth layer, and a residual module is added horizontally to the encoder and decoder of each layer. This model is used to conduct targeted research on the automatic segmentation method of rectal cancer. [H. Gao et\u00a0al., Rectal tumor segmentation method based on U-Net improved model, J. Comput. Appl.40(8) (2020) 2392\u20132397] also improved U-Net and used the same dataset as this paper, but the Dice coefficient of all targets was only 83.15%, and the Dice coefficient of small targets was only 87.17%. This paper evaluates the improved MR-U-Net network model with the three indicators of precision, recall and Dice coefficient, and finds that in comparison to Ref.\u00a0 4 the precision is 95.13%, 2.29% higher than the former work, recall is 94.28%, higher than the former work by 0.34%, Dice coefficient of all targets is 88.45%, increased by 5.3% compared with the former work, and the small targets Dice coefficient is increased by 1.28%, which is the best optimization state of this paper. Experiments show that for datasets with extremely skewed positive and negative samples, the MR-U-Net network structure after improving the hyperparameters in the optimizer can more accurately segment the rectal CT tumor lesion area. <\/jats:p>","DOI":"10.1142\/s0218001422500069","type":"journal-article","created":{"date-parts":[[2022,3,21]],"date-time":"2022-03-21T04:59:57Z","timestamp":1647838797000},"source":"Crossref","is-referenced-by-count":3,"title":["A Rectal CT Tumor Segmentation Method Based on Improved U-Net"],"prefix":"10.1142","volume":"36","author":[{"given":"Haowei","family":"Dong","sequence":"first","affiliation":[{"name":"School of Computer and Information Engineering, Nantong Institute of Technology, Nantong, Jiangsu, P. R. 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