Semi Automatic Segmentation of a Rat Brain Atlas

A common approach to segment an MRI dataset is to use a standard atlas to identify different regions of interest. Existing 2D atlases, prepared by freehand tracings of templates, are seldom complete for 3D volume segmentation. Although many of these atlases are prepared in graphics packages like Adobe Illustrator® (AI), which present the geometrical entities based on their mathematical description, the drawings are not numerically robust. This work presents an automatic conversion of graphical atlases suitable for further usage such as creation of a segmented 3D numerical atlas. The system begins with DXF (Drawing Exchange Format) files of individual atlas drawings. The drawing entities are mostly in cubic spline format. Each segment of the spline is reduced to polylines, which reduces the complexity of data. The system merges overlapping nodes and polylines to make the database of the drawing numerically integrated, i.e. each location within the drawing is referred by only one point, each line is uniquely defined by only two nodes, etc. Numerous integrity diagnostics are performed to eliminate duplicate or overlapping lines, extraneous markers, open-ended loops, etc. Numerically intact closed loops are formed using atlas labels as seed points. These loops specify the boundary and tissue type for each area. The final results preserve the original atlas with its 1272 different neuroanatomical regions which are complete, non-overlapping, contiguous sub-areas whose boundaries are composed of unique polyline

Segmentation Of Ultisequence Medical Images Using Random Walks Algorithm And Rough Sets Theory

Segmentasi imej Magnetic Resonance (MR) merupakan satu tugas klinikal yang mencabar. Selalunya, satu jenis imej MR tidak mencukupi untuk memberikan maklumat yang lengkap mengenai sesuatu tisu patologi atau objek visual dari imej Accurate Magnetic Resonance (MR) image segmentation is a clinically challenging task. More often than not, one type of MRI image is insufficient to provide the complete information about a pathological tissue or a visual object from the imag