A Hybrid System for the Semantic Annotation of Sulco-Gyral Anatomy in MRI Images

Abstract

Abstract. This paper presents an interactive system for the annotation of brain anatomical structures in Magnetic Resonance Images. The system is based on hybrid knowledge and techniques. First, it exploits both numerical knowledge from atlases and symbolic knowledge from a ruleextended ontology represented in OWL, the Web ontology language, and combines them with graphical data about cortical sulci, automatically extracted from the images. Second, the annotations of the parts of gyri and of sulci located in a region of interest are obtained with different reasoning techniques: Constraint Satisfaction Solving and Description Logics techniques. Preliminary experiments have been achieved on normal and also pathological data. The results obtained so far are very promising.

Using image mapping towards biomedical and biological data sharing

“…Spatial entities are identified together with spatial relationships among them to represent the image. Mechouche et al [ 25 ] present a method to describe spatial relations between sulci and gyri of the brain cortical structure by using the following terms: anteriorTo, posteriorTo, superiorTo, inferiorTo, lateralTo and medialTo . Hudelot et al [ 26 ] present a method to compute the implementation of spatial relations terms such as right_Of, left_Of, close_to, very_close_to, external boundary and internal boundary to describe the brain cerebral.…”

A Hybrid System Using Symbolic and Numeric Knowledge for the Semantic Annotation of Sulco-Gyral Anatomy in Brain MRI Images

“…SPAMs are 3D probabilistic maps associated with particular anatomical structures. The value at each voxel position represents the probability of belonging to this structure at that location [17]. The SPAMs were derived from a database of 305 normal subjects, after re-alignment of MRI data into a common reference system (called stereotaxic space).…”

DoctorEye: A multifunctional open platform for fast annotation and visualization of tumors in medical images

“…Numerous existing projects are Manuscript developing specialized platforms and tools to speed up the process of data analysis in different biomedical applications. Such medical image-annotation representative systems include VANO [1], CMAS [2], Hybrid System [3], Annotor [4] and Amiravis [5].…”