Klaus Spitzer

Survey: interpolation methods in medical image processing

Image interpolation techniques often are required in medical imaging for image generation (e.g., discrete back projection for inverse Radon transform) and processing such as compression or resampling. Since the ideal interpolation function spatially is unlimited, several interpolation kernels of finite size have been introduced. This paper compares 1) truncated and windowed sine; 2) nearest neighbor; 3) linear; 4) quadratic; 5) cubic B-spline; 6) cubic; g) Lagrange; and 7) Gaussian interpolation and approximation techniques with kernel sizes from 1/spl times/1 up to 8/spl times/8. The comparison is done by: 1) spatial and Fourier analyses; 2) computational complexity as well as runtime evaluations; and 3) qualitative and quantitative interpolation error determinations for particular interpolation tasks which were taken from common situations in medical image processing. For local and Fourier analyses, a standardized notation is introduced and fundamental properties of interpolators are derived. Successful methods should be direct current (DC)-constant and interpolators rather than DC-inconstant or approximators. Each methods parameters are tuned with respect to those properties. This results in three novel kernels, which are introduced in this paper and proven to be within the best choices for medical image interpolation: the 6/spl times/6 Blackman-Harris windowed sinc interpolator, and the C2-continuous cubic kernels with N=6 and N=8 supporting points. For quantitative error evaluations, a set of 50 direct digital X-rays was used. They have been selected arbitrarily from clinical routine. In general, large kernel sizes were found to be superior to small interpolation masks. Except for truncated sine interpolators, all kernels with N=6 or larger sizes perform significantly better than N=2 or N=3 point methods (p/spl Lt/0.005). However, the differences within the group of large-sized kernels were not significant. Summarizing the results, the cubic 6/spl times/6 interpolator with continuous second derivatives, as defined in (24), can be recommended for most common interpolation tasks. It appears to be the fastest six-point kernel to implement computationally. It provides eminent local and Fourier properties, is easy to implement, and has only small errors. The same characteristics apply to B-spline interpolation, but the 6/spl times/6 cubic avoids the intrinsic border effects produced by the B-spline technique. However, the goal of this study was not to determine an overall best method, but to present a comprehensive catalogue of methods in a uniform terminology, to define general properties and requirements of local techniques, and to enable the reader to select that method which is optimal for his specific application in medical imaging.

Blended learning positively affects students’ satisfaction and the role of the tutor in the problem-based learning process: results of a mixed-method evaluation

Problem-based learning (PBL) is an established didactic approach in medical education worldwide. The impact of PBL depends on the tutors’ quality and the students’ motivation. To enhance students’ motivation and satisfaction and to overcome the problems with the changing quality of tutors, online learning and face-to-face classes were systematically combined resulting in a blended learning scenario (blended problem-based learning—bPBL). The study aims at determining whether bPBL increases the students’ motivation and supports the learning process with respect to the students’ cooperation, their orientation, and more reliable tutoring. The blended PBL was developed in a cooperation of students and teachers. The well-established Seven Jump-scheme of PBL was carefully complemented by eLearning modules. On the first training day of bPBL the students start to work together with the online program, but without a tutor, on the final training day the tutor participates in the meeting for additional help and feedback. The program was evaluated by a mixed-method study. The traditional PBL course was compared with the blended PBL by means of qualitative and quantitative questionnaires, standardized group interviews, and students’ test results. In addition log-files were analyzed. A total of 185 third-year students and 14 tutors took part in the study. Motivation, subjective learning gains and satisfaction achieved significantly higher ratings by the bPBL students compared with the students learning by traditional PBL. The tutors’ opinion and the test results showed no differences between the groups. Working with the web-based learning environment was assessed as very good by the students. According to the log-file analysis, the web-based learning module was frequently used and improved the cooperation during the self-directed learning.

Addendum: B-spline interpolation in medical image processing

Analyzes B-spline interpolation techniques of degree 2, 4, and 5 with respect to all criteria that have been applied to evaluate various interpolation schemes in a recently published survey on image interpolation in medical imaging (Lehmann et al., 1999). It is shown that high-degree B-spline interpolation has superior Fourier properties, smallest interpolation error, and reasonable computing times. Therefore, high-degree B-splines are preferable interpolators for numerous applications in medical image processing, particularly if high precision is required. If no aliasing occurs, this result neither depends on the geometric transform applied for the tests nor the actual content of images.

A general discrete contour model in two, three, and four dimensions for topology-adaptive multichannel segmentation

We present a discrete contour model for the segmentation of image data with any dimension of image domain and value range. The model consists of a representation using simplex meshes and a mechanical formulation of influences that drive an iterative segmentation. The objects representation as well as the influences are valid for any dimension of the image domain. The image influences introduced here, can combine information from independent channels of higher-dimensional value ranges. Additionally, the topology of the model automatically adapts to objects contained in images. Noncontextual tests have validated the ability of the model to reproducibly delineate synthetic objects. In particular, images with a signal to noise ratio of SNR /spl les/ 0.5 are delineated within two pixels of their ground truth contour. Contextual validations have shown the applicability of the model for medical image analysis in image domains of two, three, and four dimensions in single as well as multichannel value ranges.

Extended Query Refinement for Medical Image Retrieval

The impact of image pattern recognition on accessing large databases of medical images has recently been explored, and content-based image retrieval (CBIR) in medical applications (IRMA) is researched. At the present, however, the impact of image retrieval on diagnosis is limited, and practical applications are scarce. One reason is the lack of suitable mechanisms for query refinement, in particular, the ability to (1) restore previous session states, (2) combine individual queries by Boolean operators, and (3) provide continuous-valued query refinement. This paper presents a powerful user interface for CBIR that provides all three mechanisms for extended query refinement. The various mechanisms of man–machine interaction during a retrieval session are grouped into four classes: (1) output modules, (2) parameter modules, (3) transaction modules, and (4) process modules, all of which are controlled by a detailed query logging. The query logging is linked to a relational database. Nested loops for interaction provide a maximum of flexibility within a minimum of complexity, as the entire data flow is still controlled within a single Web page. Our approach is implemented to support various modalities, orientations, and body regions using global features that model gray scale, texture, structure, and global shape characteristics. The resulting extended query refinement has a significant impact for medical CBIR applications.

Colour texture analysis for quantitative laryngoscopy.

Objective—Whilst considerable progress has been made in enhancing the quality of indirect laryngoscopy and image processing, the evaluation of clinical findings is still based on the clinicians judgement. The aim of this paper was to examine the feasibility of an objective computer-based method for evaluating laryngeal disease. Material and Methods—Digitally recorded images obtained by 90 degree- and 70 degree-angled indirect rod laryngoscopy using standardized white balance values were made of 16 patients and 19 healthy subjects. The digital images were evaluated manually by the clinician based on a standardized questionnaire, and suspect lesions were marked and classified on the image. Following colour separation, normal vocal cord areas as well as suspect lesions were analyzed automatically using co-occurrence matrices, which compare colour differences between neighbouring pixels over a predefined distance. Results—Whilst colour histograms did not provide sufficient information for distinguishing between healthy and diseased tissues, consideration of the blue content of neighbouring pixels enabled a correct classification in 81.4% of cases. If all colour channels (red, green and blue) were regarded simultaneously, the best classification correctness obtained was 77.1%. Conclusions—Although only a very basic classification differentiating between healthy and diseased tissue was attempted, the results showed progress compared to grey-scale histograms, which have been evaluated before. The results document a first step towards an objective, machine-based classification of laryngeal images, which could provide the basis for further development of an expert system for use in indirect laryngoscopy.

How to configure blended problem based learning–Results of a randomized trial

Background: Problem based learning (PBL) may be successfully complemented by Blended Learning approaches. However, the precise effect of combining different eLearning components in PBL-courses is yet unclear. Aim: This study aims at comparing the effects of the different combinations of three interactive components (Wiki, Chat, and, Interactive Diagnostic Context – a diagnostic related link collection to expert sources) on learning, aspects of group process, and individual learner satisfaction. Methods: A mixed-method study addressed all possible combinations of the three components. Tests and controls were assigned by group randomization. Hypotheses were tested by the Friedman- and the Mann–Whitney U test. Results: The results prove Wiki to positively influence the ratings given by students to the course, whereas no evidence supports the expected advantages of Chat. The Interactive Diagnostic Context led to only few significant effects concerning the diagnostic approach and general score. Conclusion: Blended PBL (bPBL) profits best from supporting asynchronous communication (i.e. Wiki). Synchronous communication components and hypothesis-driven information retrieval do not yield further improvements. Thus, bPBL should concentrate on technically fostering the group process and avoid overloading the course configuration by other eLearning components.

Scale-independent shape analysis for quantitative cytology using mathematical morphology

A system for automatic quantification of morphological changes of cell lines, proposed for cytotoxicity tests of biomaterials, is presented. Light-micrographs of cultured cells are segmented by adaptive thresholding within a local adaptive window. Connected cells in binarized micrographs are separated by a novel morphological multiscale method, treating cells in their size-specific scale and hence resulting in scale-independent separations. Significant shape descriptors correlating well with cell toxicity are extracted from single cells. Size and compactness distributions turned out to be reliable and useful parameters, providing an alternative to the common subjective grading of shape deformations by visual inspection. The system is evaluated for several standardized toxical reference substances and is now in use for clinical biocompatibility testing.

Similarity of Medical Images Computed from Global Feature Vectors for Content-Based Retrieval

Global features describe the image content by a small number of numerical values, which are usually combined into a vector of less than 1,024 components. Since color is not present in most medical images, grey-scale and texture features are analyzed in order to distinguish medical imagery from vari- ous modalities. The reference data is collected arbitrarily from radiological rou- tine. Therefore, all anatomical regions and biological systems are present and all images have been captured in various directions. The ground truth is estab- lished by manually reference coding with respect to a mono-hierarchical unam- biguous coding scheme. Based on 6,335 images, experiments are performed for 54 and 57 categories or 70 and 81 categories focusing on radiographs only or considering all images, respectively. A maximum classification accuracy of 86% was obtained using the winner-takes-all rule and a one nearest neighbor classifier. If the correct category is only required to be within the 5 or 10 best matches, we yield a best rate of 98% using normalized cross correlation of small image icons.

Evaluation of free non-diagnostic DICOM software tools

A variety of software exists to interpret files or directories compliant to the Digital Imaging and Communications in Medicine (DICOM) standard and display them as individual images or volume rendered objects. Some of them offer further processing and analysis features. The surveys that have been published so far are partly not up-to-date anymore, and neither a detailed description of the software functions nor a comprehensive comparison is given. This paper aims at evaluation and comparison of freely available, non-diagnostic DICOM software with respect to the following aspects: (i) data import; (ii) data export; (iii) header viewing; (iv) 2D image viewing; (v) 3D volume viewing; (vi) support; (vii) portability; (viii) workability; and (ix) usability. In total, 21 tools were included: 3D Slicer, AMIDE, BioImage Suite, DicomWorks, EViewBox, ezDICOM, FPImage, ImageJ, JiveX, Julius, MedImaView, MedINRIA, MicroView, MIPAV, MRIcron, Osiris, PMSDView, Syngo FastView, TomoVision, UniViewer, and XMedCon. Our results in table form can ease the selection of appropriate DICOM software tools. In particular, we discuss use cases for the inexperienced user, data conversion, and volume rendering, and suggest Syngo FastView or PMSDView, DicomWorks or XMedCon, and ImageJ or UniViewer, respectively.