The small brain structure called "hippocampus" is importantly involved
in memory mechanisms. Changes in the size and/or tissue structure
of the hippocampus have been demonstrated in such diverse disorders as
Alzheimer's dementia, partial complex epilepsy, depression, Cushing's
syndrome and chronic stress. Determination of
the contour of the hippocampus from MR images is therefore of great
importance in several clinical situations such as, e.g., the
preoperative investigation of patients with therapy resistent epilepsy
and the prediction of further cognitive decline in patients with MCI
(mild cognitive disorder). However, such a determination by visual
inspection of the images ("manual segmentation") is very time-consuming
and, furthermore, gives different results in the hands of different
Many research groups are therefore trying to find a way of
automatically delimiting the hippocampus from MRI data. This is however
a difficult task since the hippocampus borders to several different
kinds of tissue, and
since the border is not even always visible. Within our project,
several approaches have been tested; see Starck et al (2002),
Pettersson et al (2006). The latter paper is a pilot study
using a new non-rigid registration technique, the so-called morphon
, for finding the hippocampal borders.
For lack of funding, the development of our automatic method has been put on hold after that study.
Within the project, we have also developed a new computer assisted
manual method, Hipposegm,
segmentation and volumetry of the hippocampus and other brain
structures. It has up til now been applied to three different clinical
populations, including one with MCI and mild dementia (Eckerström et al
2007, 2008, 2010), and one where the patients had had inadvertent
radiation to the basal brain because of radiation treatment of cancer
in the head and neck region (Olsson et al, submitted). Several other
studies are planned in detail and will start as soon as funding becomes
available. The manual segmentation data from the clinical studies will
be used to train the automatic method if and when we get
the opportunities to develop our ideas in this field further.
The project leaders are Helge
, Department of Philosophy, GU) and Hans Knutsson
Biomedical Engineeering, Linköping University). Among our project
partners are Magnus Borga
Linköping Department), Sven Ekholm
(University of Rochester) and Göran
(Department of Diagnostic Radiology, Göteborg). The main funding for the project has come from the Swedish Research
M. Borga, H. Malmgren & H. Knutsson, FSED - feature
selective edge detection. In Proceedings of 15th International
Conference on Pattern Recognition, volume 1, 229–232, Barcelona,
Spain 2000. IAPR.
G. Starck, M. Borga, M. Friberg, E. Olsson, S. Ribbelin, H. Knutsson,
S. Ekholm & H. Malmgren, Fully automatic
segmentation of the hippocampus in MR images. Poster presentation
at ESMRMB 2002: 19th Annual Meeting of the European Society for
Magnetic Resonance in Medicine and Biology. (JPEG format).
J. Pettersson, H. Knutsson & M. Borga, Normalised
Convolution and Morphons for Non-Rigid Registration. Proceedings of
the SSBA Symposium on Image Analysis. Umeå, Sweden: SSBA, 2006.
C. Eckerström, E. Olsson, S. Rolstad, Å. Edman, A. Wallin
& H. Malmgren, The
Göteborg MCI study - absolute and normalized hippocampal volumes
in the prediction of dementia. Poster presented at Svenska
Läkaresällskapets Riksstämma, Nov. 28-30, 2007. (Pdf
C. ; Olsson, E. ; Borga, M. et al (2008). Small baseline volume of
left hippocampus is associated with subsequent conversion of MCI into
dementia. The Göteborg MCI study. Journal of the Neurological Sciences 272 (1-2) s. 48-59.
C. ; Andreasson, U. ; Olsson, E. et al (2010). Combining hippocampal
volume and CSF biomarkers improves predictive value in MCI. Dementia and Geriatric Cognitive Disorders 29, s. 294-300.
E., Eckerström, C., Berg, G. et al, Hippocampal volumes in patients
exposed to low dose radiation to the basal brain. Submitted.
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Last update: April 9, 2010 by Helge Malmgren