{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T07:15:02Z","timestamp":1769584502780,"version":"3.49.0"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2019,8,14]],"date-time":"2019-08-14T00:00:00Z","timestamp":1565740800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,8,14]],"date-time":"2019-08-14T00:00:00Z","timestamp":1565740800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["(No.81571773, 81781771943)"],"award-info":[{"award-number":["(No.81571773, 81781771943)"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Med Syst"],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1007\/s10916-019-1429-8","type":"journal-article","created":{"date-parts":[[2019,8,14]],"date-time":"2019-08-14T01:20:01Z","timestamp":1565745601000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Colorectal Cancer Diagnostic Algorithm Based on Sub-Patch Weight Color Histogram in Combination of Improved Least Squares Support Vector Machine for Pathological Image"],"prefix":"10.1007","volume":"43","author":[{"given":"Kai","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bi","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Yi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingsheng","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,8,14]]},"reference":[{"key":"1429_CR1","doi-asserted-by":"crossref","unstructured":"Hong, Y., Wei, H, and Zeng-Li, L., Research for the colon cancer based on the EMD and LS-SVM[C]. Fourth International Conference on Intelligent Computation Technology & Automation. IEEE Computer Society, 24(7):329-331, 2011.","DOI":"10.1109\/ICICTA.2011.223"},{"issue":"1 Supplement","key":"1429_CR2","doi-asserted-by":"publisher","first-page":"613","DOI":"10.1007\/s12032-010-9663-4","volume":"28","author":"H Wang","year":"2011","unstructured":"Wang, H., and Huang, G., Application of support vector machine in cancer diagnosis[J]. Med. Oncol. 28(1 Supplement):613\u2013618, 2011.","journal-title":"Med. Oncol."},{"issue":"15","key":"1429_CR3","doi-asserted-by":"publisher","first-page":"2580","DOI":"10.1080\/00032719.2014.915410","volume":"47","author":"H Chen","year":"2014","unstructured":"Chen, H., Tan, C., Wu, H. et al., Feasibility of rapid diagnosis of colorectal cancer by near-infrared spectroscopy and support vector machine[J]. Anal. Lett. 47(15):2580\u20132593, 2014.","journal-title":"Anal. Lett."},{"key":"1429_CR4","unstructured":"Mizaku, A, and Land, W. H., Biomolecular feature selection of colorectal cancer microarray data using GA-SVM hybrid and noise perturbation to address overfitting[J]. Dissertations & Theses -Gradworks, 12(1):64-76, 2009."},{"issue":"1","key":"1429_CR5","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1016\/j.media.2012.08.003","volume":"17","author":"Toru Tamaki","year":"2013","unstructured":"Tamaki, T., Yoshimuta, J., Kawakami, M. et al., Computer-aided colorectal tumor classification in NBI endoscopy using local features[J]. Med. Image Anal. 17(1):123-129, 2013.","journal-title":"Medical Image Analysis"},{"issue":"4","key":"1429_CR6","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1016\/j.engappai.2006.01.011","volume":"19","author":"S Li","year":"2006","unstructured":"Li, S., Fevens, T., Krzy Ak, A. et al., Automatic clinical image segmentation using pathological modeling, PCA and SVM[J]. Eng. Appl. Artif. Intell. 19(4):403\u2013410, 2006.","journal-title":"Eng. Appl. Artif. Intell."},{"key":"1429_CR7","unstructured":"Shi, W., Dongkai, J., Ke, W., Application of modified wavelet features and multi-class sphere SVM to pathological vocal detection[C]. Seventh International Conference on Natural Computation. IEEE, pp:1290-1298, 2011."},{"key":"1429_CR8","doi-asserted-by":"crossref","unstructured":"Majhi, B., Dash, R., and Nayak, D. R., Stationary wavelet transform and AdaBoost with SVM based pathological brain detection in MRI scanning[J]. CNS Neurol. Disord. Drug Targets 16(2):32-44, 2017.","DOI":"10.2174\/1871527315666161024142036"},{"key":"1429_CR9","unstructured":"Cataldo, S. D., Ficarra, E., and Macii, E., Automated discrimination of pathological regions in tissue images: Unsupervised clustering vs. supervised SVM classification[C]. International Joint Conference on Biomedical Engineering Systems and Technologies. Springer, Berlin, Heidelberg, pp:2100-2111, 2008."},{"key":"1429_CR10","doi-asserted-by":"crossref","unstructured":"Cataldo,Wang S, Huo J, et al. Bayesian Framework with Non-local and Low-rank Constraint for Image Reconstruction[C]\/\/ Journal of Physics Conference Series. pp:1-11, 2017.","DOI":"10.1088\/1742-6596\/787\/1\/012008"},{"issue":"3","key":"1429_CR11","first-page":"87","volume":"60","author":"T Shunji","year":"2000","unstructured":"Shunji, T., Junji, T., Atsuko, H. et al., Role of early phase helical CT images in the evaluation of wall invasion of colorectal cancer: Pathological correlation[J]. Nihon Igaku H\u014dshasen Gakkai Zasshi Nippon Acta Radiologica 60(3):87, 2000.","journal-title":"Nihon Igaku H\u014dshasen Gakkai Zasshi Nippon Acta Radiologica"},{"issue":"4","key":"1429_CR12","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1136\/jcp.50.4.358","volume":"50","author":"None","year":"1997","unstructured":"None, Colorectal cancer pathology reporting: A regional audit[J]. J. Clin. Pathol. 50(4):358\u2013358, 1997.","journal-title":"J. Clin. Pathol."},{"key":"1429_CR13","doi-asserted-by":"crossref","unstructured":"Xia, Kai Jian, H. S. Yin, and J. Q. Wang. \"A novel improved deep convolutional neural network model for medical image fusion.\"\u00a0Cluster Computing, 23(20):1-13, 2018.","DOI":"10.1007\/s10586-018-2026-1"},{"key":"1429_CR14","unstructured":"Song, B., Zhang, G., Wang, H., et al., A feasibility study of high order texture features with application to pathological diagnosis of colon lesions for CT Colonography[C]. Nuclear Science Symposium & Medical Imaging Conference. IEEE, 2013."},{"issue":"1\u20132","key":"1429_CR15","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1023\/A:1025667309714","volume":"53","author":"M Robnik-\u0160Ikonja","year":"2003","unstructured":"Robnik-\u0160Ikonja, M., and Kononenko, I., Theoretical and empirical analysis of ReliefF and RReliefF[J]. Mach. Learn. 53(1\u20132):23\u201369, 2003.","journal-title":"Mach. Learn."},{"issue":"2","key":"1429_CR16","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1016\/j.jbi.2010.12.003","volume":"44","author":"L Beretta","year":"2011","unstructured":"Beretta, L., Santaniello et al., Implementing ReliefF filters to extract meaningful features from genetic lifetime datasets[J]. J. Biomed. Inform. 44(2):361\u2013369, 2011.","journal-title":"J. Biomed. Inform."},{"key":"1429_CR17","doi-asserted-by":"crossref","unstructured":"Wang, C., Guan, Y., Zuo, C., et al., Value of the texture feature for solitary pulmonary nodules and mass lesions based on PET\/CT[C]. International Conference on Bioinformatics & Biomedical Engineering. 2010.","DOI":"10.1109\/ICBBE.2010.5514710"},{"key":"1429_CR18","doi-asserted-by":"crossref","unstructured":"Song, B., Zhang, G., Zhu, H., et al., A feasibility study of high order volumetric texture features for computer aided diagnosis of polyps via CT colonography[C]. Nuclear Science Symposium and Medical Imaging Conference (NSS\/MIC). pp:719-724, 2012.","DOI":"10.1109\/NSSMIC.2012.6551903"},{"issue":"6","key":"1429_CR19","doi-asserted-by":"publisher","first-page":"1021","DOI":"10.1007\/s11548-014-0991-2","volume":"9","author":"B Song","year":"2014","unstructured":"Song, B., Zhang, G., Lu, H. et al., Volumetric texture features from higher-order images for diagnosis of colon lesions via CT colonography[J]. Int. J. Comput. Assist. Radiol. Surg. 9(6):1021\u20131031, 2014.","journal-title":"Int. J. Comput. Assist. Radiol. Surg."},{"issue":"7","key":"1429_CR20","doi-asserted-by":"publisher","first-page":"2547","DOI":"10.1046\/j.1460-9568.2000.00109.x","volume":"12","author":"N Thon","year":"2010","unstructured":"Thon, N., Haas, C. A., Rauch, U. et al., The chondroitin sulphate proteoglycan brevican is upregulated by astrocytes after entorhinal cortex lesions in adult rats.[J]. Eur. J. Neurosci. 12(7):2547\u20132558, 2010.","journal-title":"Eur. J. Neurosci."},{"key":"1429_CR21","unstructured":"Jiang, X., Liang, Q., and Shen, T., A new color information entropy retrieval method for pathological cell image[C]\/\/ Computer & Computing Technologies in Agriculture Iv-ifip Tc 12 Conference. 0."},{"key":"1429_CR22","unstructured":"Jiang, X., Liang, Q., and Shen, T., A new color information entropy retrieval method for pathological cell image[J]. Computer and Computing Technologies in Agriculture IV, 22(12):872-880, 2016."},{"key":"1429_CR23","doi-asserted-by":"crossref","unstructured":"Xia K J, Yin H S, Zhang Y D. Deep Semantic Segmentation of Kidney and Space-Occupying Lesion Area Based on SCNN and ResNet Models Combined with SIFT-Flow Algorithm[J]. Journal of Medical Systems, 2019, 43(1):2.","DOI":"10.1007\/s10916-018-1116-1"},{"key":"1429_CR24","unstructured":"Sammouda, M, and Mukai, K., Diagnosis of liver cancer based on the analysis of pathological liver color images[C]. Medical Imaging: Image Processing. International Society for Optics and Photonics, pp:12-21, 2000."},{"key":"1429_CR25","doi-asserted-by":"crossref","unstructured":"Malekian, V., Mokhtari, M., Sadri, S., et al., Detection of collagenous colitis based on histopathology image segmentation of colon[C]\/\/ Iranian Conference on Machine Vision & Image Processing. IEEE, 2011.","DOI":"10.1109\/IranianMVIP.2011.6121589"},{"issue":"2","key":"1429_CR26","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/S1532-0464(02)00501-4","volume":"35","author":"M Sammouda","year":"2002","unstructured":"Sammouda, M., Sammouda, R., Niki, N. et al., Cancerous nuclei detection on digitized pathological lung color images[J]. J. Biomed. Inform. 35(2):92\u201398, 2002.","journal-title":"J. Biomed. Inform."},{"issue":"4","key":"1429_CR27","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1109\/TITB.2003.822952","volume":"7","author":"L Zheng","year":"2004","unstructured":"Zheng, L., Wetzel, A. W., Gilbertson, J. et al., Design and analysis of a content-based pathology image retrieval system[J]. IEEE Trans. Inf. Technol. Biomed. 7(4):249\u2013255, 2004.","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"issue":"5","key":"1429_CR28","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1007\/s10916-009-9299-0","volume":"34","author":"GB Kande","year":"2010","unstructured":"Kande, G. B., Subbaiah, P. V., and Savithri, T. S., Unsupervised fuzzy based vessel segmentation in pathological digital fundus images[J]. J. Med. Syst. 34(5):849\u2013858, 2010.","journal-title":"J. Med. Syst."},{"key":"1429_CR29","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1007\/978-3-642-23672-3_10","volume-title":"Computer Analysis of Images and Patterns","author":"Giuliana Ramella","year":"2011","unstructured":"Ramella, G., Baja, G. S. D. Color histogram-based image segmentation[M]. Computer Analysis of Images and Patterns. Springer Berlin Heidelberg, 2011."},{"key":"1429_CR30","first-page":"206","volume":"4478","author":"Y Jin","year":"2001","unstructured":"Jin, Y., Fayad, L., and Laine, A. F., Contrast enhancement by multi-scale adaptive histogram equalization[J]. Proc. SPIE Int. Soc. Opt. Eng. 4478:206\u2013213, 2001.","journal-title":"Proc. SPIE Int. Soc. Opt. Eng."}],"updated-by":[{"DOI":"10.1007\/s10916-019-1449-4","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2019,11,12]],"date-time":"2019-11-12T00:00:00Z","timestamp":1573516800000}}],"container-title":["Journal of Medical Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-019-1429-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10916-019-1429-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10916-019-1429-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,25]],"date-time":"2022-09-25T16:26:27Z","timestamp":1664123187000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10916-019-1429-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,8,14]]},"references-count":30,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2019,9]]}},"alternative-id":["1429"],"URL":"https:\/\/doi.org\/10.1007\/s10916-019-1429-8","relation":{"correction":[{"id-type":"doi","id":"10.1007\/s10916-019-1449-4","asserted-by":"object"}]},"ISSN":["0148-5598","1573-689X"],"issn-type":[{"value":"0148-5598","type":"print"},{"value":"1573-689X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,8,14]]},"assertion":[{"value":"27 February 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 July 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 August 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 November 2019","order":4,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Correction","order":5,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The original article unfortunately contained a mistake. The corresponding author\u2019s name should be corrected as \u201cYingsheng Cheng\u201d.","order":6,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"We declare that we have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human or animals participants"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}],"article-number":"306"}}