# Application of Image Fusion in Diagnosis and Treatment of Liver Cancer
## 6 Discussion on the Limitations and Prospects of Medical Image Fusion Technology  
In the modern clinical practices, physicians have a higher demand on the accuracy and efficiency of a visually-aided medical diagnostic system. The image fusion techniques can efficiently process and combine the information from different image devices, which plays an important role in the precise positioning of tumors, the early diagnosis and treatment of cancer. With the advance of modern computer systems and medical imaging equipment, image fusion technology will be further developed, bringing a new revolution to clinical diagnosis. The research trend is to develop new algorithms which will make the registration of multimodal medical images more accurate, the fusion more efficient, and thus they will eventually achieve the purpose of improving the diagnostic effect. In the following, we present several challenges and the research trend in this topic:  
Figure 5: A 25-year-old female patient with a history of colorectal cancer presented multiple liver lesions after surgery. The focal nodular hyperplasia (FNH) in the right liver shows an arterial contrast-agent enhancement (**A**), and is still hyperintense in the liver-specific contrast phase (**C**). No significant 18F-FDG-uptake is seen (**B**,**D**). A second lesion in the right liver is rated as a colorectal liver metastasis due to incomplete resection. Tumor lesion is neither detectable by MRI without liver-specific contrast phase nor with liver-specific contrast phase (**E**,**G**). In fused PET/MR images (**F**,**H**) the remaining tumor tissue lesion could clearly be identified. Additional lesions near the liver hilus are adenomas with strong arterial contrast-agent enhancement (**I**). In the liver-specific contrast phase lesions are hypointense (**K**). Similar to the FNH, no significant 18F-FDG-uptake is seen (**J**,**L**) [183]. The extensive application of different medical image modalities has played a globally recognized role in the diagnosis of the liver cancers [184]. However, these modalities still have several flaws. As a result, one research challenge and focus is to further improve the single modalities. These may include the reduction of the rising cost of these medical images, decreasing the patient's exposure time to radiation, while maintaining the image quality [185; 186]. In addition, current clinical application of image fusion is still limited to merge the medical images from two independent medical devices. As a result, the patient needs to receive multiple examinations. Consequently, image fusion is more expensive than single image technology, which limits its application in the clinical diagnosis and treatment of tumors. To reduce the examination cost and the risk of additional radiation, it is ideal to develop devices which can perform multimodalities exams at the same time while maintaining high image qualities. Development of efficient medical registration technologies is also very important. One topic is to address the significant alignment errors caused by patient breathing and motion compensation. In order to optimize linkage of the fused image, data from the unified respiratory phase should be used for registration, and the patient should remain in the same scanning position to the greatest possible extent, particularly for organs that move with the respiratory phase. Automatic registration will be the development direction of image fusion volume navigation technology, aiming to optimize the registration process and the fusion accuracy. In addition, improvement of the available algorithms in terms of accuracy and faster registration processes may promote the utility of fusion imaging. New algorithms and methods may be introduced to take into account organ movement caused by changes in breathing or position. An ideal system is based on automatic registration using complex electromagnetic tracking and computer-aided imaging algorithms, without effects on external reference points or anatomical landmarks selected by the user.