PMID- 30345308
OWN - NLM
STAT- MEDLINE
DCOM- 20190123
LR  - 20190123
IS  - 2314-6141 (Electronic)
IS  - 2314-6133 (Print)
VI  - 2018
DP  - 2018
TI  - Registration-Based Organ Positioning and Joint Segmentation Method for Liver and 
      Tumor Segmentation.
PG  - 8536854
LID - 10.1155/2018/8536854 [doi]
LID - 8536854
AB  - The automated segmentation of liver and tumor from CT images is of great 
      importance in medical diagnoses and clinical treatment. However, accurate and 
      automatic segmentation of liver and tumor is generally complicated due to the 
      complex anatomical structures and low contrast. This paper proposes a 
      registration-based organ positioning (ROP) and joint segmentation method for 
      liver and tumor segmentation from CT images. First, a ROP method is developed to 
      obtain liver's bounding box accurately and efficiently. Second, a joint 
      segmentation method based on fuzzy c-means (FCM) and extreme learning machine 
      (ELM) is designed to perform coarse liver segmentation. Third, the coarse 
      segmentation is regarded as the initial contour of active contour model (ACM) to 
      refine liver boundary by considering the topological information. Finally, tumor 
      segmentation is performed using another ELM. Experiments on two datasets 
      demonstrate the performance advantages of our proposed method compared with other 
      related works.
FAU - Jiang, Huiyan
AU  - Jiang H
AUID- ORCID: 0000-0002-1428-8776
AD  - Department of Software College, Northeastern University, Shenyang 110819, China.
FAU - Li, Shaojie
AU  - Li S
AUID- ORCID: 0000-0003-1004-9986
AD  - Department of Sino-Dutch Biomedical and Information Engineering School, 
      Northeastern University, Shenyang 110819, China.
FAU - Li, Siqi
AU  - Li S
AD  - Department of Software College, Northeastern University, Shenyang 110819, China.
LA  - eng
PT  - Journal Article
DEP - 20180924
PL  - United States
TA  - Biomed Res Int
JT  - BioMed research international
JID - 101600173
SB  - IM
MH  - *Databases, Factual
MH  - *Fuzzy Logic
MH  - Humans
MH  - Liver/*diagnostic imaging
MH  - Liver Neoplasms/*diagnostic imaging
MH  - *Machine Learning
MH  - Tomography, X-Ray Computed/*methods
PMC - PMC6174803
EDAT- 2018/10/23 06:00
MHDA- 2019/01/24 06:00
PMCR- 2018/09/24
CRDT- 2018/10/23 06:00
PHST- 2018/04/19 00:00 [received]
PHST- 2018/07/18 00:00 [revised]
PHST- 2018/09/02 00:00 [accepted]
PHST- 2018/10/23 06:00 [entrez]
PHST- 2018/10/23 06:00 [pubmed]
PHST- 2019/01/24 06:00 [medline]
PHST- 2018/09/24 00:00 [pmc-release]
AID - 10.1155/2018/8536854 [doi]
PST - epublish
SO  - Biomed Res Int. 2018 Sep 24;2018:8536854. doi: 10.1155/2018/8536854. eCollection 
      2018.