TY - GEN
T1 - Can SPHARM-Based Features from Automated or Manually Segmented Hippocampi Distinguish Between MCI and TLE?
AU - Liedlgruber, Michael
AU - Butz, Kevin
AU - Höller, Yvonne
AU - Kuchukhidze, Georgi
AU - Taylor, Alexandra
AU - Thomschevski, Aljoscha
AU - Tomasi, Ottavio
AU - Trinka, Eugen
AU - Uhl, Andreas
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Spherical Harmonics (SPHARM), when computed from hippocampus segmentations, have been shown to be useful features for discriminating patients with mild cognitive impairment (MCI) from healthy controls. In this paper we use this approach to discriminate patients with temporal lobe epilepsy (TLE) from healthy controls and for the first time, we aim to discriminate TLE patients from MCI ones. When doing so, we assess the impact of (i) using three different automated hippocampus segmentation techniques and (ii) three human raters with different qualification providing manual segmentation labels. We find that (only a fusion of) the considered automated segmentation tools deliver segmentation data which can finally be used to discriminate TLE from MCI, but for discriminating TLE from healthy controls automated techniques do not help. Further, the qualification of human segmenters has a decisive impact on the outcome of subsequent SPHARM-based classification, especially for distinguishing TLE from healthy controls (which is obviously the more difficult task).
AB - Spherical Harmonics (SPHARM), when computed from hippocampus segmentations, have been shown to be useful features for discriminating patients with mild cognitive impairment (MCI) from healthy controls. In this paper we use this approach to discriminate patients with temporal lobe epilepsy (TLE) from healthy controls and for the first time, we aim to discriminate TLE patients from MCI ones. When doing so, we assess the impact of (i) using three different automated hippocampus segmentation techniques and (ii) three human raters with different qualification providing manual segmentation labels. We find that (only a fusion of) the considered automated segmentation tools deliver segmentation data which can finally be used to discriminate TLE from MCI, but for discriminating TLE from healthy controls automated techniques do not help. Further, the qualification of human segmenters has a decisive impact on the outcome of subsequent SPHARM-based classification, especially for distinguishing TLE from healthy controls (which is obviously the more difficult task).
KW - Hippocampus segmentation
KW - MCI
KW - Spherical Harmonics
KW - TLE
UR - http://www.scopus.com/inward/record.url?scp=85066892358&partnerID=8YFLogxK
UR - http://www.mendeley.com/research/spharmbased-features-automated-manually-segmented-hippocampi-distinguish-between-mci-tle
U2 - 10.1007/978-3-030-20205-7_38
DO - 10.1007/978-3-030-20205-7_38
M3 - Conference contribution
AN - SCOPUS:85066892358
SN - 9783030202040
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 465
EP - 476
BT - Image Analysis - 21st Scandinavian Conference, SCIA 2019, Proceedings
A2 - Sintorn, Ida-Maria
A2 - Felsberg, Michael
A2 - Forssén, Per-Erik
A2 - Unger, Jonas
PB - Springer Verlag
CY - Cham
T2 - 21st Scandinavian Conference on Image Analysis, SCIA 2019
Y2 - 11 June 2019 through 13 June 2019
ER -