# Augmented Reality in Surgical Navigation: A Review of Evaluation and Validation Metrics
## 4 Discussion  
### Limitations  
In the last 20 years, augmented reality has been used in medical operations to aid physicians in understanding and performing procedures, as well as for training and planning. However, as other review papers have pointed out, AR has yet to attain its full potential in terms of utility and deployment in the medical workflow. Many reasons have been given for this; one is that the AR system design approach is primarily technology driven, necessitating the development of clinically useful AR applications. Another reason is the lack of meaningful assessments of planned AR systems to prove their benefits across the range of medical care [95]. The key challenges in evaluating AR technology include comparing results with and without the AR system, assuming that there will be a statistically significant difference in results attributable to the use of the navigation system, which is also not easy to achieve or demonstrate. It should also be emphasized that, in the AR environment, a common concern for any surgeon is that the target organ may not behave as intended. All the organs in the human body are not rigid; they deform in response to heartbeat and respiratory rhythms, laparoscopic insufflation pressure, and when physically probed [96]. These physical conditions are more noticeable during surgery on the liver and intestines (pliable organs) than the surgery on the bones and brain (semi-rigid organs) [97]. These deformations result in registration problems during surgery, which is one of the factors limiting the usage of AR technology. This is due to the fact that actual surgical confirmation of AR would include medically exposing the concealed structures revealed by the augmentation without modifying the scene or shifting the structures, which is highly unlikely in these conditions. In AR surgical applications, the tracking of calibrated tools is a basic necessity. In tracking and calibration, the use of error analysis techniques and numerical methods established for registration purposes has numerous purposes [98; 99]. Registration methods have been used in tracking to improve target design, predict tracking error, and improve  
Figure 9: Various parameters to be taken into consideration while performing the evaluation and validation study of AR systems. tracking accuracy [100]. Given the widespread usage of calibrated tools in augmented reality surgical applications, there is a lot of opportunity for expanded use of registration techniques in calibration [101; 102]. Based on the review completed in [103], there is also a need to build adequate segmentation algorithms to overcome the limits of existing methodologies and imaging modalities. It can be challenging to select the best metric for a certain image processing task. The work described in [104] highlights some of the most common faults in the most often used reference-based validation criteria in image processing. It is crucial to validate biomedical image analysis algorithms in order to advance understanding and put methodological research into implementation. Validation metrics, or the metrics by which system's performance is measured, are a crucial part of the validation design phase. In addition, to improve the accuracy of current AR systems, more research is required in the fusion of different imaging modalities, increasing bio-mechanical modeling, and improving image processing and tracking technologies [21]. Efforts should be made to improve the setup of AR systems, creating them to be more user friendly throughout all stages of surgery (microscopic and macroscopic) and also across different surgical procedures. The virtual models must be refined so that they perfectly blend with the real environment. Finally, new imaging modalities such as intra-operative ultrasound or MRI have the potential to add new details to virtual models as well as improve registration.