{"version":1,"kind":"Article","sha256":"","slug":"596","location":"","dependencies":[],"doi":"10.54294/1uhwld","frontmatter":{"title":"Contrast Enhancement for Liver Tumor Identification","abstract":"In CT images, tumors located in a liver are generally identified by intensity difference between tumor and liver. The intensity of the tumor can be lower and or higher than that of the liver. However, the main problem of liver tumor detection from is related to low contrast between tumor and liver intensities. Tumor sometimes presents in a very small dimension and makes the detection even more difficult. In this work, we focus on contrast enhancement of CT images containing liver and tumor based on the histogram processing as a necessary preprocessing for liver tumor identification. Results show that using our proposed method, the contrast of the CT images can be enhanced and results in relatively accurate identification of tumors in the liver.","license":"You are licensing your work to Kitware Inc. under the\nCreative Commons Attribution License Version 3.0.\n\nKitware Inc. agrees to the following:\n\nKitware is free\n * to copy, distribute, display, and perform the work\n * to make derivative works\n * to make commercial use of the work\n\nUnder the following conditions:\n\\\"by Attribution\\\" - Kitware must attribute the work in the manner specified by the author or licensor.\n\n * For any reuse or distribution, they must make clear to others the license terms of this work.\n * Any of these conditions can be waived if they get permission from the copyright holder.\n\nYour fair use and other rights are in no way affected by the above.\n\nThis is a human-readable summary of the Legal Code (the full license) available at\nhttp://creativecommons.org/licenses/by/3.0/legalcode","keywords":["tumor liver","contrast enhancement","histogram processing"],"authors":[{"name":"Nugroho, Hanung Adi","email":"hanungadin@gmail.com","affiliations":["Universiti Teknologi Petronas"],"corresponding":true},{"name":"Ihtatho, Dani","affiliations":[]},{"name":"Nugroho, Hermawan","affiliations":[]}],"date_submitted":"2008-07-08T13:10:03Z","external_publication_id":596,"revision_cids":["bafkreigeoh3xcvxuy2yosrj2t4eze47you4l75b4owt3kdb4tygcjbo4l4"]},"mdast":{"type":"root"},"downloads":[{"url":"https://ipfs.desci.com/ipfs/bafkreiacx7vap4isiflj7423seh3mheu4jyccujfv7vhol6skey65dolla","title":"root/reviews.md","filename":"reviews.md","extra":{"size_bytes":455,"type":"file"}},{"url":"https://ipfs.desci.com/ipfs/bafkreieitc3stxjniv7dtafnlkuuiszgaejjm7e7set7tbosq6t7smjoru","title":"root/insight-journal-metadata.json","filename":"insight-journal-metadata.json","extra":{"size_bytes":6113,"type":"file"}},{"url":"https://dweb.link/ipfs/bafkreibunkh3cnoskxm2ve3zmlnvwen434debnn6u7tso6a6r3wtndc5tm","title":"root/article.pdf","filename":"article.pdf","extra":{"size_bytes":357134,"type":"file"}}],"references":{"cite":{"order":["ref1","ref2","ref3","ref4","ref5","ref6","ref7","ref8","ref9"]},"data":{"ref1":{"label":"ref1","enumerator":"1","url":"https://doi.org/10.3322/canjclin.57.1.43","html":"2007+57+43+66+A. Jemal+R. Siegel+E. Ward+T. Murray+J. Xu+Thun"},"ref2":{"label":"ref2","enumerator":"2","html":"2002+W. R. Hendee+E.R. Ritenour"},"ref3":{"label":"ref3","enumerator":"3","url":"https://doi.org/10.1109/10.678613","html":"An Automatic Diagnostic System for CT Liver Image Classification+IEEE Trans. Biomed. Eng+45+1998+E.L. Chen+P.C. Chung+C.L. Chen+H.M. Tsai+C.I. Chang"},"ref4":{"label":"ref4","enumerator":"4","url":"https://doi.org/10.1109/tnb.2003.813930","html":"On the Accurate Counting of Tumor Cells+IEEE Trans. Bioscience+2+94+103+2003+F. Bin+W. Hsu+Mong Li+L."},"ref5":{"label":"ref5","enumerator":"5","url":"https://doi.org/10.1016/s1386-5056(98)00162-2","html":"Virtual Planning of Liver Resections:Image Processing, Visualization+Int. J. Med. Informatics+53+225+1999+G. Glombitza+W. Lamade+A.M. Demiris+M.R. Gopfert+A. Mayer+M.L. Bahner+H.P. Meinzer+G. Ritchter+T. Lehnert+C. Herfarth+Volumetric Evaluation"},"ref6":{"label":"ref6","enumerator":"6","url":"https://doi.org/10.1109/adcom.2006.4289897","html":"Wavelet based Texture Analysis of Liver Tumor from Computed Tomography Images for Characterization Using Linear Vector Quantization Neural Network+International Conference on Advanced Computing and Communications 267-270+2006+K. Mala+Sadasivam"},"ref7":{"label":"ref7","enumerator":"7","html":"1992+R. C. Gonzales+R. E.: Digital Woods+Image Processing. Addison-Wesley Longman Publishing"},"ref8":{"label":"ref8","enumerator":"8","url":"https://doi.org/10.1201/9781420042382","html":"Handbook of Computer Vision Algorithms in Image Algebra+2000+G. X. Ritter+J. N."},"ref9":{"label":"ref9","enumerator":"9","url":"https://doi.org/10.1109/tsmc.1979.4310076","html":"A Threshold Selection Method from Gray-Level Histograms+IEEE Transactions on Systems, Man, and Cybernetics+9+62+66+1979+Otsu"}}}}