TY - GEN
T1 - A novel computer aided detection (CADe) scheme for colonic polyps based on the structure decomposition
AU - Wang, Huafeng
AU - Li, Lihong
AU - Peng, Hao
AU - Han, Hao
AU - Song, Bowen
AU - Wang, Yunhong
AU - Gu, Xianfeng
AU - Liang, Zhengrong
PY - 2013
Y1 - 2013
N2 - Accurately detecting small polyps (ranged from 5~8mm) on the colon wall is of great significance for early diagnosis colorectal cancers. However, colon usually consists of the mucosa layers which result in partial volume effect (PVE) on the colon wall. Consequently, the task of computer aided detection (CADe) of polyps turns into too complicated to be reached by simply following solo philosophy. In order to achieve the mission of small polyps' detection, we propose a novel global structure decomposition approach in this paper. That is, the complex colon was separated into much uniform broken parts by means of analysis on second order derivatives of the volume image. Experimentally, we chose 60 patient cases from dataset provided by Wisconsin, and in which we focus on the polyps whose size range from 5~8mm to validate the presented new approach. Compared with previously presented in the literature, the experimental results are much more promising with an average sensitivity of 0.984. Meanwhile, the false positive rate dramatically decreased to 2.2 per dataset after false positive reduction.
AB - Accurately detecting small polyps (ranged from 5~8mm) on the colon wall is of great significance for early diagnosis colorectal cancers. However, colon usually consists of the mucosa layers which result in partial volume effect (PVE) on the colon wall. Consequently, the task of computer aided detection (CADe) of polyps turns into too complicated to be reached by simply following solo philosophy. In order to achieve the mission of small polyps' detection, we propose a novel global structure decomposition approach in this paper. That is, the complex colon was separated into much uniform broken parts by means of analysis on second order derivatives of the volume image. Experimentally, we chose 60 patient cases from dataset provided by Wisconsin, and in which we focus on the polyps whose size range from 5~8mm to validate the presented new approach. Compared with previously presented in the literature, the experimental results are much more promising with an average sensitivity of 0.984. Meanwhile, the false positive rate dramatically decreased to 2.2 per dataset after false positive reduction.
KW - colon structure decomposition
KW - Colonic polyp
KW - computed tomography colonography
KW - computeraided detection
UR - https://www.scopus.com/pages/publications/84886465326
U2 - 10.1007/978-3-642-41083-3_8
DO - 10.1007/978-3-642-41083-3_8
M3 - Conference contribution
AN - SCOPUS:84886465326
SN - 9783642410826
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 63
EP - 72
BT - Abdominal Imaging
T2 - 5th International Workshop on Abdominal Imaging: Computation and Clinical Applications, Held in Conjunction with 16th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013
Y2 - 22 September 2013 through 22 September 2013
ER -