Brain Misalignment Correction Based on Vascular Structures Segmentation in Tumor Surgery using Normalized Gradient Field

A possible treatment of brain tumor consists in a surgery performed by neurosurgeons who open the skull (called craniotomy). By navigating through the brain, they reach the tumor tissues and try to remove the maximum possible. The task is tricky because of the small operation field delimited by the craniotomy, also because of the difficulty to differentiate the brain healthy tissue surrounding the tumor and the brain misalignment that occurs. An additional tool for intraoperative imaging represents therefore a crucial element to guide the navigation through the brain safely and improve the resection task. Based on blood vessels segmentation, we proposed a methodology for the correction of brain displacement during resection. This misalignment of the brain was resolved by using a Normalized Gradient Field (NGF) that allows to register segmented vessels with a good accuracy. After to test our method on data phantom and patient data, the result were validated in an average of 90%

Documenting and predicting topic changes in Computers in Biology and Medicine: A bibliometric keyword analysis from 1990 to 2017

The Computers in Biology and Medicine (CBM) journal promotes the use of com-puting machinery in the fields of bioscience and medicine. Since the first volume in 1970, the importance of computers in these fields has grown dramatically, this is evident in the diversification of topics and an increase in the publication rate. In this study, we quantify both change and diversification of topics covered in CBM. This is done by analysing the author supplied keywords, since they were electronically captured in 1990. The analysis starts by selecting 40 keywords, related to Medical (M) (7), Data (D)(10), Feature (F) (17) and Artificial Intelligence (AI) (6) methods. Automated keyword clustering shows the statistical connection between the selected keywords. We found that the three most popular topics in CBM are: Support Vector Machine (SVM), Elec-troencephalography (EEG) and IMAGE PROCESSING. In a separate analysis step, we bagged the selected keywords into sequential one year time slices and calculated the normalized appearance. The results were visualised with graphs that indicate the CBM topic changes. These graphs show that there was a transition from Artificial Neural Network (ANN) to SVM. In 2006 SVM replaced ANN as the most important AI algo-rithm. Our investigation helps the editorial board to manage and embrace topic change. Furthermore, our analysis is interesting for the general reader, as the results can help them to adjust their research directions

Vascular Structure Identification in Intraoperative 3D Contrast-Enhanced Ultrasound Data

In this paper, a method of vascular structure identification in intraoperative 3D Contrast-Enhanced Ultrasound (CEUS) data is presented. Ultrasound imaging is commonly used in brain tumor surgery to investigate in real time the current status of cerebral structures. The use of an ultrasound contrast agent enables to highlight tumor tissue, but also surrounding blood vessels. However, these structures can be used as landmarks to estimate and correct the brain shift. This work proposes an alternative method for extracting small vascular segments close to the tumor as landmark. The patient image dataset involved in brain tumor operations includes preoperative contrast T1MR (cT1MR) data and 3D intraoperative contrast enhanced ultrasound data acquired before (3D-iCEUS s t a r t ) and after (3D-iCEUS e n d ) tumor resection. Based on rigid registration techniques, a preselected vascular segment in cT1MR is searched in 3D-iCEUS s t a r t and 3D-iCEUS e n d data. The method was validated by using three similarity measures (Normalized Gradient Field, Normalized Mutual Information and Normalized Cross Correlation). Tests were performed on data obtained from ten patients overcoming a brain tumor operation and it succeeded in nine cases. Despite the small size of the vascular structures, the artifacts in the ultrasound images and the brain tissue deformations, blood vessels were successfully identified