An automatic tool to facilitate the statistical group analysis of DTI.

BACKGROUND: Users may have difficulty calculating DTI group statistics since they need to master several complex tools that require high user intervention. A tool called DTIStatistics for the automatic and easy calculation of DTI group statistics was developed to reduce analysis times and possible errors. METHODS: The proposed software was designed by using a user-centred methodology in which we performed an iterative usability evaluation with an expert committee. Once the experts׳ requirements were fulfilled, we performed a validation of the final version of DTIStatistics with target users, comparing the execution time of this tool and the standard pipeline normally used. RESULTS: Target users needed significantly less time to complete the tasks with DTIStatistics, reducing the analysis time from 1383.78 to 57.2s. They were able to complete all the tasks and barely made errors. Moreover, target users were not able to display the analysis results with the standard pipeline, but when using our tool they only needed 34s. Target users found DTIStatistics easy to learn, use and interact with, and they concluded that they could effectively complete the tasks with it. Additionally, we present example results in the study of depression to demonstrate the validity of DTIStatistics for clinical research. CONCLUSIONS: DTIStatistics facilitates and significantly automates the calculation of DTI group statistics by reducing the analysis times, which implies lower costs. DTIStatistics is highly applicable in clinical research, as demonstrated by the fact that it is currently being used at the University Hospital, University of Navarra (Spain).

Distortion correction and calibration of intra-operative spine X-ray images using a constrained DLT algorithm.

This work presents an automatic method for distortion correction and calibration of intra-operative spine X-ray images, a fundamental step for the use of this modality in computer and robotic assisted surgeries. Our method is based on a prototype calibration drum, attached to the c-arm intensifier during the intervention. The projections of its embedded fiducial beads onto the X-ray images are segmented by the proposed method, which uses its calculated centroids to undo the distortion and, afterwards, calibrate the c-arm. For the latter purpose, we propose the use of a constrained version of the well known Direct Linear Transform (DLT) algorithm, reducing its degrees of freedom from 11 to 3. Experimental evaluation of our method is included in this work, showing that it is fast and more accurate than other existing methods. The low segmentation error level also ensures accurate calibration of the c-arm, with an expected error of 4% in the computation of its focal distance.