Alexander Behrens

Extensions of H.264/AVC for Multiview Video Compression

We consider multiview video compression: the problem of jointly compressing multiple views of a scene recorded by different cameras. To take advantage of the correlation between views, we propose using disparity compensated view prediction and view synthesis and describe how these features can be implemented by extending the H.264/AVC compression standard. Finally, we discuss experimental results on the test sequences from the MPEG call for proposals on multiview video.

Classification of Colon Polyps in NBI Endoscopy using Vascularization Features

The evolution of colon cancer starts with colon polyps. There are two different types of colon polyps, namely hyperplasias and adenomas. Hyperplasias are benign polyps which are known not to evolve into cancer and, therefore, do not need to be removed. By contrast, adenomas have a strong tendency to become malignant. Therefore, they have to be removed immediately via polypectomy. For this reason, a method to differentiate reliably adenomas from hyperplasias during a preventive medical endoscopy of the colon (colonoscopy) is highly desirable. A recent study has shown that it is possible to distinguish both types of polyps visually by means of their vascularization. Adenomas exhibit a large amount of blood vessel capillaries on their surface whereas hyperplasias show only few of them. In this paper, we show the feasibility of computer-based classification of colon polyps using vascularization features. The proposed classification algorithm consists of several steps: For the critical part of vessel segmentation, we implemented and compared two segmentation algorithms. After a skeletonization of the detected blood vessel candidates, we used the results as seed points for the Fast Marching algorithm which is used to segment the whole vessel lumen. Subsequently, features are computed from this segmentation which are then used to classify the polyps. In leave-one-out tests on our polyp database (56 polyps), we achieve a correct classification rate of approximately 90%.

Creating Panoramic Images for Bladder Fluorescence Endoscopy

The medical diagnostic analysis and therapy of urinary bladder cancer based on endoscopes are state of the art in urological medicine. Due to the limited field of view of endoscopes, the physician can examine only a small part of the whole operating field at once. This constraint makes visual control and navigation difficult, especially in hollow organs. A panoramic image, covering a larger field of view, can overcome this difficulty. Directly motivated by a physician we developed an image mosaicing algorithm for endoscopic bladder fluorescence video sequences. In this paper, we present an approach which is capable of stitching single endoscopic video images to a combined panoramic image. Based on SIFT features we estimate a 2-D homography for each image pair, using an affine model and an iterative model-fitting algorithm. We then apply the stitching process and perform a mutual linear interpolation. Our panoramic image results show a correct stitching and lead to a better overview and understanding of the operation field.

Computer-based classification of small colorectal polyps by using narrow-band imaging with optical magnification

BACKGROUND Recent studies have shown that narrow-band imaging (NBI) is a powerful diagnostic tool for the differentiation between neoplastic and non-neoplastic colorectal polyps. OBJECTIVE To develop a computer-based method for classification of colorectal polyps. DESIGN A prospective study. SETTING University hospital. PATIENTS A total of 214 patients with colorectal polyps who underwent a zoom NBI colonoscopy. INTERVENTIONS A total of 434 detected polyps 10 mm or smaller were imaged and subsequently removed for histological analysis. MAIN OUTCOME MEASUREMENTS Diagnostic performance in polyp classification by 2 experts, 2 nonexperts, and a computer-based algorithm. RESULTS The expert group and the computer-based algorithm achieved a comparable diagnostic performance (expert group: 93.4% sensitivity, 91.8% specificity, and 92.7% accuracy; computer-based algorithm: 95.0% sensitivity, 90.3% specificity, and 93.1% accuracy) and were both significantly superior to the nonexpert group (86.0% sensitivity, 87.8% specificity, and 86.8% accuracy) in terms of sensitivity, negative predictive value, and accuracy. Subgroup analysis of 255 polyps 5 mm or smaller revealed comparable results without significant differences in the overall analysis of all polyps. LIMITATIONS No fully automatic classification system. CONCLUSIONS The study demonstrates that computer-based classification of colon polyps can be achieved with high diagnostic performance.

Local and global panoramic imaging for fluorescence bladder endoscopy

Endoscopic treatment of bladder cancer is more and more often based on photodynamic diagnostics (PDD), a specialized endoscopic technique where a narrow-band bluish illumination causes tumors to fluoresce reddish. Contrast between tumors and healthy bladder tissue is thus noticeably increased compared to white light endoscopy. A downside of PDD is the low illumination power, which requires that the distance between endoscope and bladder wall be kept low, thus resulting in a small field of view (FOV). We therefore describe an approach to combine several successive frames into a local PDD panorama, which provides a larger and sufficiently bright FOV for treatment. Furthermore, the endoscopic cancer treatment generally starts with a complete scan of the bladder to detect the tumors. For diagnosis, navigation and reporting, a global overview image of the bladder wall is often desired. While construction of such a global panorama can be based on the same algorithm as the local panorama, direct planar visualization of the sphere-shaped bladder may cause severe distortions. Apart from the global panorama computation itself, we therefore analyze these distortions, and provide an alternative visualization which is based on bladder depictions used in standard reporting forms and anatomy textbooks.

Real-time image composition of bladder mosaics in fluorescence endoscopy

Today, photodynamic diagnostics is commonly used in endoscopic intervention of the urinary bladder. Excited by a narrow band illumination, fluorescence markers enhance the visual contrast between benign and malignant tissue. Since in this modality the endoscope must be moved close to the bladder wall to provide sufficiently exposed images, the field of view (FOV) of the endoscope is very limited. This impedes the navigation and the re-identifying of multi-focal tumors for the physician. Thus, an image providing a larger FOV, composed from single images is highly desired during the intervention for surgery assistance. Since endoscopic mosaicking in real-time is still an open issue, we introduce a new feature-based image mosaicking algorithm for fluorescence endoscopy. Using a multi-threaded software design, the extraction of SURF features, the matching and the image stitching are separated in single processing threads. In an optimization step we discuss the trade-off between feature repeatability and processing time. After adjusting an optimal thread synchronization, the optimal workload of each thread results in a fast and real-time capable computation of image mosaics. On a standard hardware platform our algorithm performs within the RealTimeFrame framework with an update rate of 8.17 frames per second at full input image resolution (780×576). Providing a fast growing image with an extended FOV during the intervention, the mosaic displayed on a second monitor promises high potential for surgery assistance.

A Comparison of Blood Vessel Features and Local Binary Patterns for Colorectal Polyp Classification

Colorectal cancer is the third leading cause of cancer deaths in the United States of America for both women and men. By means of early detection, the five year survival rate can be up to 90%. Polyps can to be grouped into three different classes: hyperplastic, adenomatous, and carcinomatous polyps. Hyperplastic polyps are benign and are not likely to develop into cancer. Adenomas, on the other hand, are known to grow into cancer (adenoma-carcinoma sequence). Carcinomas are fully developed cancers and can be easily distinguished from adenomas and hyperplastic polyps. A recent narrow band imaging (NBI) study by Tischendorf et al. has shown that hyperplastic polyps and adenomas can be discriminated by their blood vessel structure. We designed a computer-aided system for the differentiation between hyperplastic and adenomatous polyps. Our development aim is to provide the medical practitioner with an additional objective interpretation of the available image data as well as a confidence measure for the classification. We propose classification features calculated on the basis of the extracted blood vessel structure. We use the combined length of the detected blood vessels, the average perimeter of the vessels and their average gray level value. We achieve a successful classification rate of more than 90% on 102 polyps from our polyp data base. The classification results based on these features are compared to the results of Local Binary Patterns (LBP). The results indicate that the implemented features are superior to LBP.

Automated classification of colon polyps in endoscopic image data

Colon cancer is the third most commonly diagnosed type of cancer in the US. In recent years, however, early diagnosis and treatment have caused a significant rise in the five year survival rate. Preventive screening is often performed by colonoscopy (endoscopic inspection of the colon mucosa). Narrow Band Imaging (NBI) is a novel diagnostic approach highlighting blood vessel structures on polyps which are an indicator for future cancer risk. In this paper, we review our automated inter- and intra-observer independent system for the automated classification of polyps into hyperplasias and adenomas based on vessel structures to further improve the classification performance. To surpass the performance limitations we derive a novel vessel segmentation approach, extract 22 features to describe complex vessel topologies, and apply three feature selection strategies. Tests are conducted on 286 NBI images with diagnostically important and challenging polyps (10mm or smaller) taken from our representative polyp database. Evaluations are based on ground truth data determined by histopathological analysis. Feature selection by Simulated Annealing yields the best result with a prediction accuracy of 96.2% (sensitivity: 97.6%, specificity: 94.2%) using eight features. Future development aims at implementing a demonstrator platform to begin clinical trials at University Hospital Aachen.

A Multi-threaded Mosaicking Algorithm for Fast Image Composition of Fluorescence Bladder Images

The treatment of urinary bladder cancer is usually carried out using fluorescence endoscopy. A narrow-band bluish illumination activates a tumor marker resulting in a red fluorescence. Because of low illumination power the distance between endoscope and bladder wall is kept low during the whole bladder scan, which is carried out before treatment. Thus, only a small field of view (FOV) of the operation field is provided, which impedes navigation and relocating of multi-focal tumors. Although off-line calculated panorama images can assist surgery planning, the immediate display of successively growing overview images composed from single video frames in real-time during the bladder scan, is well suited to ease navigation and reduce the risk of missing tumors. Therefore we developed an image mosaicking algorithm for fluorescence endoscopy. Due to fast computation requirements a flexible multi-threaded software architecture based on our RealTimeFrame platform is developed. Different algorithm tasks, like image feature extraction, matching and stitching are separated and applied by independent processing threads. Thus, different implementation of single tasks can be easily evaluated. In an optimization step we evaluate the trade-off between feature repeatability and total processing time, consider the thread synchronization, and achieve a constant workload of each thread. Thus, a fast computation of panoramic images is performed on a standard hardware platform, preserving full input image resolution (780x576) at the same time. Displayed on a second clinical monitor, the extended FOV of the image composition promises high potential for surgery assistance.

First Steps into Practical Engineering for Freshman Students Using MATLAB and LEGO Mindstorms Robots

Besides lectures on basic theoretical topics, contemporary teaching and learning concepts for first semester students give more and more consideration to practically motivated courses. In this context, a new first-year introductory course in practical engineering has been established in the first semester curriculum of Electrical Engineering at RWTH Aachen University, Germany. Based on a threefold learning concept, programming skills in MATLAB are taught to 309 students within a full-time block course laboratory. The students are encouraged to transfer known mathematical basics to program algorithms and real-world applications performed by 100 LEGO Mindstorms robots. A new MATLAB toolbox and twofold project tasks have been developed for this purpose by a small team of supervisors. The students are supervised by over 60 tutors at 23 institutes, and are encouraged to create their own robotics applications. We describe how the laboratory motivates the students to act and think like engineers and to solve real-world issues with limited resources. The evaluation results show that the proposed practical course concept successfully boosts students’ motivation, advances their programming skills, and encourages the peer learning process.