S Sveta Zinger

GPU-accelerated real-time free-viewpoint DIBR for 3DTV

Multi-view 3D video may succeed stereo 3DTV in multimedia and TV applications. The MPEG committee has installed a special task force to establish a standard for multiview 3D video coding. Enabling free-viewpoint selection by the consumer is one of the major purposes of multi-view 3D encoded data. One focal point of our research work concerns an efficient implementation of the rendering part of stereoscopic free-viewpoint visualization, which is a computationally expensive task and significantly determines the final image quality. The free-viewpoint DIBR algorithm that is described in this article is implemented with an off-theshelf GPU that can be integrated in advanced 3DTV systems. We present the principal steps of a representative freeviewpoint DIBR, based on image warping and image artifact reduction techniques, and show the key differences between the reference software and our GPU implementation. One of those differences is the joint execution of signal processing blocks to share memory usage. Using a combination of the highly parallel programming architecture CUDA and a graphics API, we have achieved real-time performance executing 1080p HD multi-view video with a rendering quality that is comparable to the software implementation.

Supportive automatic annotation of early esophageal cancer using local gabor and color features

Over the past years High Definition (HD) endoscopy has become a crucial tool for the early detection of esophageal cancer. The high resolution offers specialist physicians high-quality visual information, enabling them to identify dysplastic tissue leading to Early Adenocarcinoma (EAC). The detection and removal of these early types of cancer drastically increases the survival chances of the patient. However, even for an experienced specialist it remains an arduous task to identify the patterns associated with early cancer. Therefore, a computer-aided detection system that supports the physician seems highly attractive. We present a novel algorithm for automatic detection of early cancerous tissue in HD endoscopic images. The algorithm computes local color- and texture features based on the original and on the Gabor-filtered image. We explore the spectral characteristics of the image regions that contain early cancer and we design appropriate filters based on this analysis. The features are classified by a trained Support Vector Machine (SVM) after which additional post-processing techniques are applied in order to annotate the image region containing early cancer. For 7 patients, we compare 32 annotations made by the algorithm with the corresponding delineations made by an expert gastroenterologist. Of 38 lesions indicated independently by the gastroenterologist, the system detects 36 of those lesions with a recall of 0.95 and a precision of 0.75.

Quality improving techniques in DIBR for free-viewpoint video

This paper evaluates our 3D view interpolation rendering algorithm and proposes a few performance improving techniques. We aim at developing a rendering method for free-viewpoint 3DTV, based on depth image warping from surrounding cameras. The key feature of our approach is warping texture and depth in the first stage simultaneously and postpone blending the new view to a later stage, thereby avoiding errors in the virtual depth map. We evaluate the rendering quality in two ways. Firstly, it is measured by varying the distance between the two nearest cameras. We have obtained a PSNR gain of 3 dB and 4.5 dB for the ‘Breakdancers’ and ‘Ballet’ sequences, respectively, compared to the performance of a recent algorithm. A second series of tests in measuring the rendering quality were performed using compressed video or images from surrounding cameras. The overall quality of the system is dominated by rendering quality and not by coding.

View Interpolation for Medical Images on Autostereoscopic Displays

We present an approach for efficient rendering and transmitting views to a high-resolution autostereoscopic display for medical purposes. Displaying biomedical images on an autostereoscopic display poses different requirements than in a consumer case. For medical usage, it is essential that the perceived image represents the actual clinical data and offers sufficiently high quality for diagnosis or understanding. Autostereoscopic display of multiple views introduces two hurdles: transmission of multi-view data through a bandwidth-limited channel and the computation time of the volume rendering algorithm. We address both issues by generating and transmitting limited set of views enhanced with a depth signal per view. We propose an efficient view interpolation and rendering algorithm at the receiver side based on texture+depth data representation, which can operate with a limited amount of views. We study the main artifacts that occur during rendering-occlusions, and we quantify them first for a synthetic model and then for real-world biomedical data. The experimental results allow us to quantify the peak signal-to-noise ratio for rendered texture and depth as well as the amount of disoccluded pixels as a function of the angle between surrounding cameras.

Technical aspects of neurostimulation: Focus on equipment, electric field modeling, and stimulation protocols

Neuromodulation is a field of science, medicine, and bioengineering that encompasses implantable and non-implantable technologies for the purpose of improving quality of life and functioning of humans. Brain neuromodulation involves different neurostimulation techniques: transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), vagus nerve stimulation (VNS), and deep brain stimulation (DBS), which are being used both to study their effects on cognitive brain functions and to treat neuropsychiatric disorders. The mechanisms of action of neurostimulation remain incompletely understood. Insight into the technical basis of neurostimulation might be a first step towards a more profound understanding of these mechanisms, which might lead to improved clinical outcome and therapeutic potential. This review provides an overview of the technical basis of neurostimulation focusing on the equipment, the present understanding of induced electric fields, and the stimulation protocols. The review is written from a technical perspective aimed at supporting the use of neurostimulation in clinical practice.

Transition to adult medical care for adolescents with epilepsy

INTRODUCTION During transition to adult medical care, the adolescent with epilepsy is especially prone to emotional, mental, physical, and social developmental difficulties, leading to stigma and poor psychosocial and socioeconomic outcome in the long term. OBJECTIVES The aim of this review is twofold: to describe the psychosocial and medical transition from adolescence to adulthood and to evaluate the most effective model for transitional services in adolescents with epilepsy. METHODS We searched PubMed for quantitative and qualitative data about transition from adolescence to adulthood in patients with epilepsy. RESULTS A total of 49 articles were retrieved. We reviewed personal, psychosocial, and medical issues during transition and their long-term individual and societal consequences. Identifying risk factors for poor transition can lead to appropriate interventions for patients and their family. Although the concept of multidisciplinary transition care for adolescents with epilepsy is widely recognized, only a few transition clinics have been established. There is lack of evidence for their quality and cost-effectiveness. CONCLUSION In addition to medical problems, more attention should be paid to the risk of psychosocial problems during transition from pediatric to adult care. The implementation of transition care for adolescents with epilepsy is considered beneficial; however, its effectiveness should be further investigated.

Text-image alignment for historical handwritten documents

We describe our work on text-image alignment in context of building a historical document retrieval system. We aim at aligning images of words in handwritten lines with their text transcriptions. The images of handwritten lines are automatically segmented from the scanned pages of historical documents and then manually transcribed. To train automatic routines to detect words in an image of handwritten text, we need a training set - images of words with their transcriptions. We present our results on aligning words from the images of handwritten lines and their corresponding text transcriptions. Alignment based on the longest spaces between portions of handwriting is a baseline. We then show that relative lengths, i.e. proportions of words in their lines, can be used to improve the alignment results considerably. To take into account the relative word length, we define the expressions for the cost function that has to be minimized for aligning text words with their images. We apply right to left alignment as well as alignment based on exhaustive search. The quality assessment of these alignments shows correct results for 69% of words from 100 lines, or 90% of partially correct and correct alignments combined.

Evaluation of a multidisciplinary epilepsy transition clinic for adolescents

INTRODUCTION The main goal of the transition clinic is to explore and optimize medical issues during transition from adolescence to adulthood, and to ease the transition into adult care. However, only limited data on the process and outcomes of transitional care in clinical practice are available. OBJECTIVE To describe the process and outcomes of an Epilepsy Transition Clinic in a tertiary referral center in The Netherlands. METHODS Data were collected from patients with epilepsy (aged 15-25 years), who visited the transition clinic between March 2012 and September 2014. RESULTS The Epilepsy Transition Clinic is staffed with a multidisciplinary team including a neurologist/epileptologist, clinical neuropsychologist, a social worker and an educationalist/occupational counselor, all with knowledge of paediatric and adult medical and developmental issues. In total, 117 patients with epilepsy were included in the analysis. After consultation, 89 patients received a diagnostic work-up (76.1%), change in AED prescription (n = 64, 54.7%), or consultation/tailored advice (n = 73, 62.4%). In fourteen patients (12.0%) the epilepsy diagnosis was changed. Nineteen patients (16.2%) had complete epilepsy remission for over one year. Forty-three patients (36.8%) were referred to adult care. CONCLUSION This study describes a multidisciplinary epilepsy transition clinic staffed by a neurologist/epileptologist, neuropsychologist, a social worker and an educationalist/occupational counselor. Diagnostic work-up and evaluation of psychosocial and educational/vocational status during adolescence are strongly recommended.

Computer-aided detection of early neoplastic lesions in Barrett's esophagus.

BACKGROUND AND STUDY AIMS Early neoplasia in Barretts esophagus is difficult to detect and often overlooked during Barretts surveillance. An automatic detection system could be beneficial, by assisting endoscopists with detection of early neoplastic lesions. The aim of this study was to assess the feasibility of a computer system to detect early neoplasia in Barretts esophagus. PATIENTS AND METHODS Based on 100 images from 44 patients with Barretts esophagus, a computer algorithm, which employed specific texture, color filters, and machine learning, was developed for the detection of early neoplastic lesions in Barretts esophagus. The evaluation by one endoscopist, who extensively imaged and endoscopically removed all early neoplastic lesions and was not blinded to the histological outcome, was considered the gold standard. For external validation, four international experts in Barretts neoplasia, who were blinded to the pathology results, reviewed all images. RESULTS The system identified early neoplastic lesions on a per-image analysis with a sensitivity and specificity of 0.83. At the patient level, the system achieved a sensitivity and specificity of 0.86 and 0.87, respectively. A trade-off between the two performance metrics could be made by varying the percentage of training samples that showed neoplastic tissue. CONCLUSION The automated computer algorithm developed in this study was able to identify early neoplastic lesions with reasonable accuracy, suggesting that automated detection of early neoplasia in Barretts esophagus is feasible. Further research is required to improve the accuracy of the system and prepare it for real-time operation, before it can be applied in clinical practice.

Performance-efficient architecture for free-viewpoint 3DTV receiver

This paper presents algorithmic and architectural solutions for a free-viewpoint 3DTV receiver system. We describe our rendering algorithm and evaluate performance-related challenges in mapping of the algorithm on a receiver board of which the architecture is outlined. It is found that the required processing load exceeds the provisioning of dual Virtex5 FPGAs. We develop several mapping optimizations to fit the rendering algorithm into a platform.