误差修正法提高黑素体跟踪精度

Toshiaki Okabe, K. Hotta
{"title":"误差修正法提高黑素体跟踪精度","authors":"Toshiaki Okabe, K. Hotta","doi":"10.1109/DICTA.2013.6691477","DOIUrl":null,"url":null,"abstract":"This paper proposes an error correction method for improving accuracy of melanosome tracking. Melanosomes in intracellular images are tracked manually to investigate the cause of disease, and an automatic tracking method is desirable. We detect all melanosome candidates by SIFT with 2 different parameters. Of course, the SIFT also detects non- melanosomes. Therefore, we use the 4-valued difference image (4-VDimage) to eliminate non- melanosome candidates. After tracking melanosome, we track the melanosome with low confidence again from t+1 to t. If the results from t to t+1 and from t+1 to t are different, we judge that initial tracking result is a failure, the melanosome is eliminated from candidates and re-tracking is carried out. Experimental results demonstrate that our method can correct the error and improves the accuracy.","PeriodicalId":231632,"journal":{"name":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","volume":"153 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Accuracy Improvement of Melanosome Tracking by Error Correction\",\"authors\":\"Toshiaki Okabe, K. Hotta\",\"doi\":\"10.1109/DICTA.2013.6691477\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an error correction method for improving accuracy of melanosome tracking. Melanosomes in intracellular images are tracked manually to investigate the cause of disease, and an automatic tracking method is desirable. We detect all melanosome candidates by SIFT with 2 different parameters. Of course, the SIFT also detects non- melanosomes. Therefore, we use the 4-valued difference image (4-VDimage) to eliminate non- melanosome candidates. After tracking melanosome, we track the melanosome with low confidence again from t+1 to t. If the results from t to t+1 and from t+1 to t are different, we judge that initial tracking result is a failure, the melanosome is eliminated from candidates and re-tracking is carried out. Experimental results demonstrate that our method can correct the error and improves the accuracy.\",\"PeriodicalId\":231632,\"journal\":{\"name\":\"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)\",\"volume\":\"153 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DICTA.2013.6691477\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA.2013.6691477","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

为了提高黑素体跟踪的精度,提出了一种误差校正方法。在细胞内图像中的黑素小体被手动跟踪以调查疾病的原因,并且一种自动跟踪方法是可取的。我们用2个不同参数的SIFT检测所有候选黑素体。当然,SIFT也可以检测非黑素体。因此,我们使用4值差分图像(4- vimage)来消除非黑素体候选。跟踪完黑素体后,从t+1到t再次对置信度较低的黑素体进行跟踪。如果从t到t+1和从t+1到t的结果不同,则判断初始跟踪结果失败,将该黑素体从候选体中剔除,重新进行跟踪。实验结果表明,该方法能有效地修正误差,提高检测精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accuracy Improvement of Melanosome Tracking by Error Correction
This paper proposes an error correction method for improving accuracy of melanosome tracking. Melanosomes in intracellular images are tracked manually to investigate the cause of disease, and an automatic tracking method is desirable. We detect all melanosome candidates by SIFT with 2 different parameters. Of course, the SIFT also detects non- melanosomes. Therefore, we use the 4-valued difference image (4-VDimage) to eliminate non- melanosome candidates. After tracking melanosome, we track the melanosome with low confidence again from t+1 to t. If the results from t to t+1 and from t+1 to t are different, we judge that initial tracking result is a failure, the melanosome is eliminated from candidates and re-tracking is carried out. Experimental results demonstrate that our method can correct the error and improves the accuracy.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信