Biomedical subjects

Axel Pinz

Publications and source records attributed to Axel Pinz.

5 recordsLinked to original sources

PubMed2006

Robust pose estimation from a planar target.

In theory, the pose of a calibrated camera can be uniquely determined from a minimum of four coplanar but noncollinear points. In practice, there are many applications of camera pose tracking from planar targets and there is also a number of recent pose estimation algorithms which perform this task in real-time, but all of these algorithms suffer from pose ambiguities. This paper investigates the pose ambiguity for planar targets viewed by a perspective camera. We show that pose ambiguities--two distinct local minima of the according error function--exist even for cases with wide angle lenses and close range targets. We give a comprehensive interpretation of the two minima and derive an analytical solution that locates the second minimum. Based on this solution, we develop a new algorithm for unique and robust pose estimation from a planar target. In the experimental evaluation, this algorithm outperforms four state-of-the-art pose estimation algorithms.

Algorithms↗

PubMed2006

Generic object recognition with boosting.

This paper explores the power and the limitations of weakly supervised categorization. We present a complete framework that starts with the extraction of various local regions of either discontinuity or homogeneity. A variety of local descriptors can be applied to form a set of feature vectors for each local region. Boosting is used to learn a subset of such feature vectors (weak hypotheses) and to combine them into one final hypothesis for each visual category. This combination of individual extractors and descriptors leads to recognition rates that are superior to other approaches which use only one specific extractor/descriptor setting. To explore the limitation of our system, we had to set up new, highly complex image databases that show the objects of interest at varying scales and poses, in cluttered background, and under considerable occlusion. We obtain classification results up to 81 percent ROC-equal error rate on the most complex of our databases. Our approach outperforms all comparable solutions on common databases.

Algorithms↗

PubMed2003

Comparison of 4 methods for quantifying posterior capsule opacification.

PURPOSE: To compare the results of posterior capsule opacification (PCO) quantification and the repeatability of a fully automated analysis system (Automated Quantification of After-Cataract [AQUA]) with that of 2 other quantification methods and subjective grading of PCO. A test set of digital retroillumination images of 100 eyes with PCO of varying degrees was used. SETTING: Department of Ophthalmology, University of Vienna, Vienna, Austria. METHODS: One hundred digital retroillumination images of eyes (100 patients) with PCO were selected to attain an even distribution from mild to severe cases. The images were evaluated by 4 methods: subjective grading by 4 experienced and 4 inexperienced examiners, the subjective Evaluation of Posterior Capsular Opacification (EPCO) system, posterior capsule opacification (POCO) software, and the AQUA system. Ten images were presented twice to assess the reproducibility of the analysis systems. RESULTS: Subjective grading correlated best with the subjective EPCO system and the objective AQUA system (r = 0.94 and r = 0.93, respectively). The POCO system showed very early saturation and therefore a much weaker correlation (r = 0.73). The POCO scores reached the maximum of 100% in several minimal to mild PCO cases. The reproducibility of the AQUA software was perfect and that of the other analysis systems, comparably satisfactory. CONCLUSION: The objective AQUA score correlated well with subjective methods including the EPCO system. The POCO system, which assesses PCO area, did not adequately describe PCO intensity and includes a subjective step in the analysis process. The AQUA system could become an important tool for randomized masked trials of PCO inhibition.

Cataract↗

PubMed2003

Removal of reflections in the photographic assessment of PCO by fusion of digital retroillumination images.

PURPOSE: Automated image-analysis systems for objective assessment of posterior capsule opacification (PCO) depend on good image quality. One major drawback is the existence of light-reflection artifacts (Purkinje spots) in retroillumination images of the posterior capsule. Therefore, a software algorithm was developed that removes these artifacts by fusion of two or more digital images from the same eye, photographed in slightly different directions of gaze. METHODS: The image-fusion process comprises five steps: definition of a primary and a secondary image, automated segmentation of the region of interest and the Purkinje spots, manual selection of three pairs of corresponding points in both images, geometric registration and radiometric calibration of the regions to be inserted from the secondary image into the primary image. The program was tested with an image set of 30 eyes that had various degrees of PCO. A digital image acquisition system with a coaxial optical path was used to take retroillumination images from each eye in at least three different directions of gaze. RESULTS: In 28 cases all light-reflection artifacts within the capsulorrhexis rim could be removed entirely. In two cases, small parts of single Purkinje spots remained visible, because the reflections were located too closely in the primary and the secondary images. CONCLUSIONS: Fusion of digital retroillumination images provides high-quality, reflection-free PCO images. This allows objective PCO assessment systems to analyze 100% of the posterior capsule, leading to more accurate results.

Algorithms↗

PubMed2002

Reproducibility of standardized retroillumination photography for quantification of posterior capsule opacification.

PURPOSE: To determine the short-term reproducibility of standardized digital retroillumination images of regeneratory posterior capsule opacification (PCO) using the photographic setup at 1 institution. SETTING: Department of Ophthalmology, University of Vienna, Vienna, Austria. METHODS: In this prospective study, 60 retroillumination images of 30 eyes with varying degrees of PCO and different types of intraocular lenses were acquired with a standardized digital coaxial retroillumination system. Two images were taken per eye with a 1-minute interval between images. Ten other eyes were photographed in the same way but with a 5-day interval between the 2 images. All images were evaluated with a fully automated, objective PCO analysis software in which the PCO score was from 0 to 100. The 2 results (A, B) in each eye were compared, and the differences were calculated. RESULTS: There was a high correlation between the A and B results (r = 0.99). The mean absolute difference was 3.7%. The repeatability coefficient was 8.8%. CONCLUSION: Digital coaxial retroillumination photography provided quick acquisition of regeneratory PCO images. It provided excellent image quality and high reproducibility. The technique forms a good basis for automated quantification of PCO with new software systems.

Cataract↗