Atlas-based Segmentation of Tumor-bearing Brain Images

In diagnostic neuroradiology as well as in radiation oncology and neurosurgery, there is an increasing demand for accurate segmentation of tumor-bearing brain images. Atlas-based segmentation is an appealing automatic technique thanks to its robustness and versatility. However, atlas-based segmentation of tumor-bearing brain images is challenging due to the confounding effects of the tumor in the patient image. In this article, we provide a brief background on brain tumor imaging and introduce the clinical perspective, before we categorize and review the state of the art in the current literature on atlas-based segmentation for tumor-bearing brain images. We also present selected methods and results from our own research in more detail. Finally, we conclude with a short summary and look at new developments in the field, including requirements for future routine clinical use.

Speech outcome in complete unilateral cleft lip and palate - a comparison of three methods of the hard palate closure.

The aim of this study was to compare the speech in subjects with cleft lip and palate, in whom three methods of the hard palate closure were used. One hundred and thirty-seven children (96 boys, 41 girls; mean age = 12 years, SD = 1·2) with complete unilateral cleft lip and palate (CUCLP) operated by a single surgeon with a one-stage method were evaluated. The management of the cleft lip and soft palate was comparable in all subjects; for hard palate repair, three different methods were used: bilateral von Langenbeck closure (b-vL group, n = 39), unilateral von Langenbeck closure (u-vL group, n = 56) and vomerplasty (v-p group, n = 42). Speech was assessed: (i) perceptually for the presence of a) hypernasality, b) compensatory articulations (CAs), c) audible nasal air emissions (ANE) and d) speech intelligibility; (ii) for the presence of compensatory facial grimacing, (iii) with clinical intra-oral evaluation and (iv) with videonasendoscopy. A total rate of hypernasality requiring pharyngoplasty was 5·1%; total incidence post-oral compensatory articulations (CAs) was 2·2%. The overall speech intelligibility was good in 84·7% of cases. Oronasal fistulas (ONFs) occurred in 15·7% b-vL subjects, 7·1% u-vL subjects and 50% v-p subjects (P < 0·001). No statistically significant intergroup differences for hypernasality, CAs and intelligibility were found (P > 0·1). In conclusion, the speech after early one-stage repair of CUCLP was satisfactory. The method of hard palate repair affected the incidence of ONFs, which, however, caused relatively mild and inconsistent speech errors.

Patient-Specific Semi-Supervised Learning for Postoperative Brain Tumor Segmentation

In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

Interactive Segmentation of MR Images from Brain Tumor Patients

Medical doctors often do not trust the result of fully automatic segmentations because they have no possibility to make corrections if necessary. On the other hand, manual corrections can introduce a user bias. In this work, we propose to integrate the possibility for quick manual corrections into a fully automatic segmentation method for brain tumor images. This allows for necessary corrections while maintaining a high objectiveness. The underlying idea is similar to the well-known Grab-Cut algorithm, but here we combine decision forest classification with conditional random field regularization for interactive segmentation of 3D medical images. The approach has been evaluated by two different users on the BraTS2012 dataset. Accuracy and robustness improved compared to a fully automatic method and our interactive approach was ranked among the top performing methods. Time for computation including manual interaction was less than 10 minutes per patient, which makes it attractive for clinical use.

Facebook style: The use of non-standard features in virtual speech conditioned by the medium Facebook

Over the last few years Facebook has become a widespread and continuously expanding medium of communication. Being a new medium of social interaction, Facebook produces its own communication style. My focus of analysis is how Facebook users from the city of Malaga create this style by means of phonic features typical of the Andalusian variety and how the users reflect on the use of these phonic features. This project is based on a theoretical framework which combines variationist sociolinguistics with CMC to study the emergence of a style peculiar of the online social networks. In a corpus of Facebook users from three zones of Malaga, I have analysed the use of non-standard phonic features and then compared them with the same features in a reference corpus collected on three beaches of Malaga. From this comparison it can be deduced that the analysed social and linguistic factors work differently in real and virtual speech. Due to these different uses we can consider the peculiar electronic communication of Facebook as a style constrained by the electronic medium. It is a style which serves the users to create social meaning and to express their linguistic identities.

Speech Understanding with a New Implant Technology: A Comparative Study with a New Nonskin Penetrating Baha System

Objective. To compare hearing and speech understanding between a new, nonskin penetrating Baha system (Baha Attract) to the current Baha system using a skin-penetrating abutment. Methods. Hearing and speech understanding were measured in 16 experienced Baha users. The transmission path via the abutment was compared to a simulated Baha Attract transmission path by attaching the implantable magnet to the abutment and then by adding a sample of artificial skin and the external parts of the Baha Attract system. Four different measurements were performed: bone conduction thresholds directly through the sound processor (BC Direct), aided sound field thresholds, aided speech understanding in quiet, and aided speech understanding in noise. Results. The simulated Baha Attract transmission path introduced an attenuation starting from approximately 5 dB at 1000 Hz, increasing to 20–25 dB above 6000 Hz. However, aided sound field threshold shows smaller differences and aided speech understanding in quiet and in noise does not differ significantly between the two transmission paths. Conclusion. The Baha Attract system transmission path introduces predominately high frequency attenuation. This attenuation can be partially compensated by adequate fitting of the speech processor. No significant decrease in speech understanding in either quiet or in noise was found.

"Sounds Funny? – Humor Effects of Phonological and Prosodic Figures of Speech"

Whereas semantic, logical, and narrative features of verbal humor are well-researched, phonological and prosodic dimensions of verbal funniness are hardly explored. In a 2 × 2 design we varied rhyme and meter in humorous couplets. Rhyme and meter enhanced funniness ratings and supported faster processing. Rhyming couplets also elicited more intense and more positive affective responses, increased subjective comprehensibility and more accurate memory. The humor effect is attributed to special rhyme and meter features distinctive of humoristic poetry in several languages. Verses that employ these formal features make an artful use of typical poetic vices of amateurish poems written for birthday parties or other occasions. Their metrical patterning sounds “mechanical” rather than genuinely “poetic”; they also disregard rules for “good” rhymes. The processing of such verses is discussed in terms of a metacognitive integration of their poetically deviant features into an overall effect of processing ease. The study highlights the importance of nonsemantic rhetorical features in language processing.

Perception of co-speech gestures in aphasic patients: A visual exploration study during the observation of dyadic conversations.

BACKGROUND Co-speech gestures are part of nonverbal communication during conversations. They either support the verbal message or provide the interlocutor with additional information. Furthermore, they prompt as nonverbal cues the cooperative process of turn taking. In the present study, we investigated the influence of co-speech gestures on the perception of dyadic dialogue in aphasic patients. In particular, we analysed the impact of co-speech gestures on gaze direction (towards speaker or listener) and fixation of body parts. We hypothesized that aphasic patients, who are restricted in verbal comprehension, adapt their visual exploration strategies. METHODS Sixteen aphasic patients and 23 healthy control subjects participated in the study. Visual exploration behaviour was measured by means of a contact-free infrared eye-tracker while subjects were watching videos depicting spontaneous dialogues between two individuals. Cumulative fixation duration and mean fixation duration were calculated for the factors co-speech gesture (present and absent), gaze direction (to the speaker or to the listener), and region of interest (ROI), including hands, face, and body. RESULTS Both aphasic patients and healthy controls mainly fixated the speaker's face. We found a significant co-speech gesture × ROI interaction, indicating that the presence of a co-speech gesture encouraged subjects to look at the speaker. Further, there was a significant gaze direction × ROI × group interaction revealing that aphasic patients showed reduced cumulative fixation duration on the speaker's face compared to healthy controls. CONCLUSION Co-speech gestures guide the observer's attention towards the speaker, the source of semantic input. It is discussed whether an underlying semantic processing deficit or a deficit to integrate audio-visual information may cause aphasic patients to explore less the speaker's face.

The New Cockney: New Ethnicities and Adolescent Speech in the Traditional East End of London

The New Cockney provides a sociolinguistic account of speech variation among adolescents in the 'traditional' East End of London. The study takes account of the social and economic upheaval in the area since the 1950s, primarily concentrating on factors such as the immigration of the Bangladeshi community and its effect on the Cockney dialect. By paying attention to the particular, this book contributes to a better understanding of the more general concerns of linguistic variation. With a focus on the interaction and social practices of a group of adolescents attending a youth centre, the study highlights some of the possible mechanisms for language change.

The Multimodal Brain TumorImage Segmentation Benchmark (BRATS)

In this paper we report the set-up and results of the Multimodal Brain Tumor Image Segmentation Benchmark (BRATS) organized in conjunction with the MICCAI 2012 and 2013 conferences. Twenty state-of-the-art tumor segmentation algorithms were applied to a set of 65 multi-contrast MR scans of low- and high-grade glioma patients - manually annotated by up to four raters - and to 65 comparable scans generated using tumor image simulation software. Quantitative evaluations revealed considerable disagreement between the human raters in segmenting various tumor sub-regions (Dice scores in the range 74-85%), illustrating the difficulty of this task. We found that different algorithms worked best for different sub-regions (reaching performance comparable to human inter-rater variability), but that no single algorithm ranked in the top for all subregions simultaneously. Fusing several good algorithms using a hierarchical majority vote yielded segmentations that consistently ranked above all individual algorithms, indicating remaining opportunities for further methodological improvements. The BRATS image data and manual annotations continue to be publicly available through an online evaluation system as an ongoing benchmarking resource.