Computational Methods for Molecular Imaging (Lecture Notes in Computational Vision and Biomechanics)

This volume contains original submissions on the development and application of molecular imaging computing. The editors invited authors to submit high-quality contributions on a wide range of topics including, but not limited to:
• Image Synthesis & Reconstruction of Emission Tomography (PET, SPECT) and other Molecular Imaging Modalities
• Molecular Imaging Enhancement
• Data Analysis of Clinical & Pre-clinical Molecular Imaging
• Multi-Modal Image Processing (PET/CT, PET/MR, SPECT/CT, etc.)
• Machine Learning and Data Mining in Molecular Imaging.

Molecular imaging is an evolving clinical and research discipline enabling the visualization, characterization and quantification of biological processes taking place at the cellular and subcellular levels within intact living subjects. Computational methods play an important role in the development of molecular imaging, from image synthesis to data analysis and from clinical diagnosis to therapy individualization.

This work will bring readers from academia and industry up to date on the most recent developments in this field.