Accelerated organ region segmentation by the revised radial basis function network using a graphics processing unit
-
- Konishi Takeshi
- Department of Medical Informatics, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan
-
- Kondo Tadashi
- Department of Medical Image Informatics, Graduate School of Health Sciences, Tokushima University, Tokushima, Japan
-
- Moriguchi Hiroki
- Uchida Neurosurgery Clinic, Kochi, Japan
-
- Tagi Masato
- Department of Medical Informatics, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan
-
- Hirose Jun
- Department of Medical Informatics, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan
この論文をさがす
説明
<p>This study aimed to accelerate the segmentation of organs in medical imaging with the revised radial basis function (RBF) network, using a graphics processing unit (GPU). We segmented the lung and liver regions from 250 chest x-ray computed tomography (CT) images and 160 abdominal CT images, respectively, using the revised RBF network. We compared the time taken to segment images and their accuracy between serial processing by a single-core central processing unit (CPU), parallel processing using four CPU cores, and GPU processing. Segmentation times for lung and liver organ regions shortened to 57.80 and 35.35 seconds for CPU parallel processing and 20.16 and 11.02 seconds for GPU processing, compared to 211.03 and 124.21 seconds for CPU serial processing, respectively. The concordance rate of the segmented region to the normal region in slices excluding the upper and lower ends (173 lung and 111 liver slices) was 98% for lung and 96% for liver. The use of CPU parallel processing and GPU shortened the organ segmentation time in the revised RBF network without compromising segmentation accuracy. In particular, segmentation time was shortened to less than 10%with GPU. This processing method will contribute to workload reduction in imaging analysis. J. Med. Invest. 66 : 86-92, February, 2019</p>
収録刊行物
-
- The Journal of Medical Investigation
-
The Journal of Medical Investigation 66 (1.2), 86-92, 2019-02-15
国立大学法人 徳島大学医学部
- Tweet
詳細情報 詳細情報について
-
- CRID
- 1390845713063621504
-
- NII論文ID
- 130007638730
-
- NII書誌ID
- AA12022913
-
- ISSN
- 13496867
- 13431420
-
- PubMed
- 31064962
-
- 本文言語コード
- en
-
- データソース種別
-
- JaLC
- Crossref
- PubMed
- CiNii Articles
-
- 抄録ライセンスフラグ
- 使用不可