Abstract
Cell morphology measurement is important in evaluating the injury level of nervous system. However, current measurement process is mostly achieved by manual estimation which is subjective and time-consuming. We hence propose a two-stage method to automatically segment axons and myelin sheaths from microscopic images for measuring the cell morphology quantitatively. First, an automatic thresholding method is used to obtain axon candidates and then geometric and image properties are used to assure the axon regions. Second, the outer contour of myelin sheath is segmented using the active contour model with the obtained axon contour as the initial solution. Then, the desired morphological parameters can be readily measured. In the experiments, we used seven nerve images for accuracy validation and achieved very small contour distance errors (less than 0.5 μm with nerve diameter around 8 μm in average). Overall, the proposed method is found efficient and useful in nerve parameter evaluation.
| Original language | English |
|---|---|
| Title of host publication | Intelligent Information and Database Systems - 4th Asian Conference, ACIIDS 2012, Proceedings |
| Pages | 486-494 |
| Number of pages | 9 |
| Edition | PART 3 |
| DOIs | |
| Publication status | Published - 2012 Mar 27 |
| Event | 4th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2012 - Kaohsiung, Taiwan Duration: 2012 Mar 19 → 2012 Mar 21 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Number | PART 3 |
| Volume | 7198 LNAI |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 4th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2012 |
|---|---|
| Country | Taiwan |
| City | Kaohsiung |
| Period | 12-03-19 → 12-03-21 |
Fingerprint
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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Quantitative measurement of nerve cells and myelin sheaths from microscopic images via two-staged segmentation. / Liu, Yung Chun; Chen, Chih Kai; Chen, Hsin Chen; Hong, Syu Huai; Yang, Cheng Chang; Jou, I. Ming; Sun, Yung-Nien.
Intelligent Information and Database Systems - 4th Asian Conference, ACIIDS 2012, Proceedings. PART 3. ed. 2012. p. 486-494 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7198 LNAI, No. PART 3).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Quantitative measurement of nerve cells and myelin sheaths from microscopic images via two-staged segmentation
AU - Liu, Yung Chun
AU - Chen, Chih Kai
AU - Chen, Hsin Chen
AU - Hong, Syu Huai
AU - Yang, Cheng Chang
AU - Jou, I. Ming
AU - Sun, Yung-Nien
PY - 2012/3/27
Y1 - 2012/3/27
N2 - Cell morphology measurement is important in evaluating the injury level of nervous system. However, current measurement process is mostly achieved by manual estimation which is subjective and time-consuming. We hence propose a two-stage method to automatically segment axons and myelin sheaths from microscopic images for measuring the cell morphology quantitatively. First, an automatic thresholding method is used to obtain axon candidates and then geometric and image properties are used to assure the axon regions. Second, the outer contour of myelin sheath is segmented using the active contour model with the obtained axon contour as the initial solution. Then, the desired morphological parameters can be readily measured. In the experiments, we used seven nerve images for accuracy validation and achieved very small contour distance errors (less than 0.5 μm with nerve diameter around 8 μm in average). Overall, the proposed method is found efficient and useful in nerve parameter evaluation.
AB - Cell morphology measurement is important in evaluating the injury level of nervous system. However, current measurement process is mostly achieved by manual estimation which is subjective and time-consuming. We hence propose a two-stage method to automatically segment axons and myelin sheaths from microscopic images for measuring the cell morphology quantitatively. First, an automatic thresholding method is used to obtain axon candidates and then geometric and image properties are used to assure the axon regions. Second, the outer contour of myelin sheath is segmented using the active contour model with the obtained axon contour as the initial solution. Then, the desired morphological parameters can be readily measured. In the experiments, we used seven nerve images for accuracy validation and achieved very small contour distance errors (less than 0.5 μm with nerve diameter around 8 μm in average). Overall, the proposed method is found efficient and useful in nerve parameter evaluation.
UR - http://www.scopus.com/inward/record.url?scp=84863378678&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863378678&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-28493-9_51
DO - 10.1007/978-3-642-28493-9_51
M3 - Conference contribution
SN - 9783642284922
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 486
EP - 494
BT - Intelligent Information and Database Systems - 4th Asian Conference, ACIIDS 2012, Proceedings
ER -