Biomedical Engineering Reference
In-Depth Information
in the size of the corpus callosum (CC) and its subregions in patients with autism relative
to controls are well established. In this work, we aim at using the reported abnormalities
of the WM and the CC, in order to devise robust classification methods of autistic vs.
normal subjects through analyzes of their respective MRIs. To overcome the limitations
and shortcomings of the volumetric studies, our analysis is based on shape descriptions and
geometric models. A novel technique is used to compute the 3D distance map as a shape
descriptor of the WM. The distribution of this distance map is then used as a statistical
feature that allows discrimination between the two groups. Furthermore, we use our newly
proposed nonrigid registration technique based on scale space and curve evolution theories
to devise a new classification approach by analyzing the deformation fields (DF) generated
from registering CCs onto each others. For each group (autistic and control), we pick a
number of segmented CC datasets, one of which is chosen as reference and the remaining
ones registered to this reference using our registration method. The generated DFs are
averaged, and their distributions are computed to represent the changes of the magnitudes
of each group. Given a subject to be classified, we register its MR dataset, once to the
chosen control reference and then to the chosen autistic reference. The two corresponding
DFs are statistically compared to the two average DFs, representing each class, in order to
indicate the class to which the tested subject belong. The accuracy of our techniques was
tested on postmortem and in-vivo brain MR data. The results are very promising and show
that, contrary to traditional methods, the proposed techniques are less sensitive to age and
volume effects.
1.
INTRODUCTION
Autism is a complex developmental disability that typically appears during
the first three years of life and is the result of a neurological disorder that affects the
normal functioning of the brain, impacting development in the areas of social inter-
action and communication skills. Both children and adults with autism typically
show difficulties in verbal and nonverbal communications, social interactions, and
leisure or play activities. Autism is a spectrum disorder and it affects each individ-
ual differently and at varying degrees, with milder forms like Asperger syndrome,
in which intellectual ability is high but social interaction is low, and with the most
severe cases typified by unusual, self-injurious, and aggressive behaviors. Such
behaviors may persist throughout life and may inflict a heavy burden on those who
interact with autistic persons. Cognitive impairments may also last over time and
often result in mental retardation in the majority of individuals with autism [1].
Nowadays, doctors prefer the term Autistic Spectrum Disorder (ASD) to refer to
autism.
Autism is not a rare disorder, as once was thought. According to the Centers
for Disease Control and Prevention (CDC), about 1 in 166 American children
fall somewhere within the autistic spectrum [4]. Although the cause of autism
is still largely not clear, researchers have suggested that genetic, developmental,
and environmental factors may be the cause or the predisposing effects toward
developing autism [5, 6, 7]. No current cure is specifically designed for autism.
However, there are some therapies or interventions designed to remedy specific
symptoms in each individual. These therapies are educational, behavioral, or skill-
