Background The postoperative imaging assessment of Cochlear Implant (CI) patients is imperative. The main obstacle is that Magnetic Resonance imaging (MR) is contraindicated or hindered by significant artefacts in most cases with CIs. This study describes an automatic cochlear image registration and fusion method that aims to help radiologists and surgeons to process pre-and postoperative 3D multimodal imaging studies in cochlear implant (CI) patients. Methods and findings We propose a new registration method, Automatic Cochlea Image Registration (ACIR-v3), which uses a stochastic quasi-Newton optimiser with a mutual information metric to find 3D rigid transform parameters for registration of preoperative and postoperative CI imaging. The method was tested against a clinical cochlear imaging dataset that contains 131 multimodal 3D imaging studies of 41 CI patients with preoperative and postoperative images. The preoperative images were MR, Multidetector Computed Tomography (MDCT) or Cone Beam Computed Tomography (CBCT) while the postoperative were CBCT. The average root mean squared error of ACIR-v3 method was 0.41 mm with a standard deviation of 0.39 mm. The results were evaluated quantitatively using the mean squared error of two 3D landmarks located manually by two neuroradiology experts in each image and compared to other previously known registration methods, e.g. Fast Preconditioner Stochastic Gradient Descent, in terms of accuracy and speed. Conclusions Our method, ACIR-v3, produces high resolution images in the postoperative stage and allows for visualisation of the accurate anatomical details of the MRI with the absence of significant metallic artefacts. The method is implemented as an open-source plugin for 3D Slicer tool.

This article proposes a study of degrees of latency of the agent, which is a semantic role performed by a participant of the communicative situation described in a sentence; this role correlates with the instigator of the action. The agent can be expressed explicitly, so that everybody understands who the action is performed by, or in a hidden, latent way. Drawing on Goatly’s (2018) research which demonstrates that degrees of agent’s latency can vary, we modify his scale of latency by taking into consideration non-verbal (visual) means. A great societal concern for environmental issues around the globe nowadays, together with the ecolinguistic vector of this research account for its timeliness. The purpose of this research is to identify the degrees of latency of the agent of environmental discourse. Syntactic constructions, lexical units, and visual images that render the agent were chosen as the object-matter of analysis, while the degrees of latency – as its subject-matter. The methods comprise general scientific methods, such as induction and deduction, synthesis and analysis, observation and contrast, as well as linguistic methods proper: critical discourse analysis, semantic analysis, and multimodal analysis. The sample is selected from online versions of most widely read British newspapers, both broadsheets and tabloids, The Guardian and Metro respectively. A modified scale of degrees of agent’s latency is suggested, where six categories of linguistic means are differentiated according to the degree of their latency. Explicit predication is characterized by a zero degree of latency; its measure increases in grammatical constructions, tropes, nominalizations, ellipsis, and indefinite agent respectively. The prospects of this research lie in comparison and quantitative counts of the agent’s latency in different types of British media.