Cancer is one of the leading causes of death all over the world. The research of cancer has been significant in the medical imaging community, since modern imaging technology, for example, molecular imaging, has already enhanced cancer management, including early detection, more accurate diagnosis, better treatment planning, and treatment monitoring in early stage. Molecular imaging is the in vivo visualization and measurement of biological process at the cellular and molecular level. It allows not only localization of tumor lesions but also visualization of the expression and activity of specific molecules, which have great influence on tumor behavior and response to treatment. Many different modalities, such as MRI, SPECT, and PET, have been developed and used for noninvasive molecular imaging and have played a central role in clinical oncology. However, due to large intersubject variability and variety of many parameters in molecular images, it is generally difficult to apply the same analytic method or simple equations to describe the targets such as lesions and anatomies in the images. Hence, in order to facilitate further the application of molecular imaging in clinical oncology, image processing techniques have been widely applied to the detection of cancer, characterization and segmentation of tumor lesions, planning of cancer treatment, evaluation of the effectiveness of treatment, and prognostication of cancer, etc. Therefore, research in medical imaging has been focused on the advanced image processing techniques, in order to make better use of the rich information in the molecular image data.

The aim of this special issue is to bring together researchers working on image processing and cancer molecular imaging and to publish high-quality papers in this field. We welcome original papers and review articles that will focus on the latest application of image processing techniques in multimodality cancer molecular imaging. The topics of interest in this special issue include all aspects of image processing research for cancer molecular imaging.

Potential topics include but are not limited to the following:

• Pharmacokinetic modeling approaches
• Computer-aided detection/diagnosis of cancer
• Treatment evaluation and prognostication of cancer
• Segmentation/delineation of tumor lesions
• Coregistration or fusion of multimodality molecular images (e.g., MRI/PET, MRI/CT)
• Correlation between molecular image data and other medical data of cancer (e.g., genotype, phenotype) from a medical perspective, for profiled description of the imaged cancer type(s)
• Advantages and limitations of existing and new imaging processing software/techniques
• The importance of molecular image processing within the entire cycle of cancer patient management (i.e., prospective studies for strategic planning/pretreatment, concurrent studies for key points of treatment, and retrospective studies for posttreatment)
• Other image processing techniques applied in cancer molecular imaging