Development of automatic detection application for bone metastases in X-ray CT images
Development of automatic detection application for bone metastases in X-ray CT images
批准号:
24800017
负责人:
HANAOKA Shouhei
金额:
$1.91万
依托单位:
依托单位国家:
日本
项目类别:
Grant-in-Aid for Research Activity Start-up
财政年份:
2012
资助国家:
日本
项目状态:
已结题
起止时间:
2012-08-31 至 2014-03-31
中文摘要
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英文摘要
1. A segmentation method for vertebral bone regions was developed. In the method, five landmarks are detected on each vertebra and these landmark positions are used to initialize the following multi-atlas-based segmentation method which can segment regions of all vertebrae simultaneously.2. A rough detection and displaying method for bone metastasis regions is developed. The method is based on the temporal subtraction between the recent CT images and the older CT images.3. A database which includes 35 subjects with multiple bone metastases was established. In each subject, the metastasis regions were inputted manually in a 3-dimensional manner.
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Automatic categorization of anatomical landmark-local appearances based on diffeomorphic emons and spectral clustering for constructing detector ensembles
基于微分同胚和谱聚类的解剖地标局部外观自动分类,用于构建探测器集合
DOI:
--
发表时间:
2012
期刊:
影响因子:
--
作者:
[内田寛邦, 位高啓史, 宮田完二郎, 石井武彦, 西山伸宏, 片岡一則, Shouhei Hanaoka]
通讯作者:
Shouhei Hanaoka
Semiautomatic segmentation of whole-spinal vertebrae in CT volumes by multi-atlas method : accuracy improvement by using anatomical landmark position information
通过多图谱方法对 CT 体积中的整个脊柱进行半自动分割:通过使用解剖标志位置信息提高准确性
DOI:
--
发表时间:
2014
期刊:
影响因子:
--
作者:
[S Hanaoka, Y Masutani, M Nemoto, Y Nomura, S Miki, T Yoshikawa, N Hayashi, and K Ohtomo]
通讯作者:
and K Ohtomo
Automated detection of anomalous spinal segmenta- tions : A feasibility study by using 300 CT datasets
自动检测异常脊柱分段:使用 300 个 CT 数据集进行可行性研究
DOI:
--
发表时间:
2014
期刊:
影响因子:
--
作者:
[Y Nakano, S Hanaoka, M Nemoto, Y Masutani, N Hayashi, and K Ohtomo]
通讯作者:
and K Ohtomo
A multiple anatomical landmark detection system for body CT images
身体CT图像的多解剖标志检测系统
DOI:
--
发表时间:
2013
期刊:
影响因子:
--
作者:
[S Hanaoka, M Nemoto, Y Nomura, S Miki, Yoshikawa, N Hayashi, K Ohtomo, and Y Masutani]
通讯作者:
and Y Masutani
Semiautomatic segmentation of whole-spinal vertebrae in CT volumes by multi-atlas method: accuracy improvement by using anatomical landmark position information
通过多图谱方法对 CT 体积中的整个脊柱进行半自动分割:利用解剖标志位置信息提高精度
DOI:
--
发表时间:
2014
期刊:
影响因子:
--
作者:
[Shouhei Hanaoka, Mitsutaka Nemoto, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Kuni Ohtomo, Yoshitaka Masutani]
通讯作者:
Yoshitaka Masutani
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