[Information improving secondary evaluation procedures in neuroradiology]

Area of Science:

• Neuroradiology
• Medical Imaging
• Computer Science

Background:

• Computer and software systems significantly impact computer-assisted image processing in neuroradiology.
• Applications are crucial for advancing diagnostic and therapeutic capabilities.

Purpose of the Study:

• To provide an overview of current and future applications of computer-assisted image processing in neuroradiology.
• To highlight the importance of segmentation as a foundational technique.

Main Methods:

• Segmentation for isolating anatomical structures.
• Image analysis including planimetry, volumetry, and angle calculation.
• Three-dimensional (3D) imaging for surgical and stereotactic planning.
• Image fusion for integrating multimodal data (morphological and functional).

Main Results:

• Segmentation is fundamental for other image processing methods.
• Image analysis tools enable objective monitoring of disease progression.
• 3D imaging aids in precise surgical and stereotactic approach planning.
• Image fusion facilitates simultaneous presentation of diverse imaging data, particularly morphological and functional parameters.

Conclusions:

• Computer-assisted image processing is invaluable in clinical neuroradiology.
• The integration of segmentation, analysis, 3D imaging, and fusion offers significant benefits.
• Future applications promise further advancements in neuroradiological diagnostics and treatment planning.