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.

Fusion of fundus images and MRI data of the human eye

Purpose Ophthalmologists are confronted with a set of different image modalities to diagnose eye tumors e.g., fundus photography, CT and MRI. However, these images are often complementary and represent pathologies differently. Some aspects of tumors can only be seen in a particular modality. A fusion of modalities would improve the contextual information for diagnosis. The presented work attempts to register color fundus photography with MRI volumes. This would complement the low resolution 3D information in the MRI with high resolution 2D fundus images. Methods MRI volumes were acquired from 12 infants under the age of 5 with unilateral retinoblastoma. The contrast-enhanced T1-FLAIR sequence was performed with an isotropic resolution of less than 0.5mm. Fundus images were acquired with a RetCam camera. For healthy eyes, two landmarks were used: the optic disk and the fovea. The eyes were detected and extracted from the MRI volume using a 3D adaption of the Fast Radial Symmetry Transform (FRST). The cropped volume was automatically segmented using the Split Bregman algorithm. The optic nerve was enhanced by a Frangi vessel filter. By intersection the nerve with the retina the optic disk was found. The fovea position was estimated by constraining the position with the angle between the optic and the visual axis as well as the distance from the optic disk. The optical axis was detected automatically by fitting a parable on to the lens surface. On the fundus, the optic disk and the fovea were detected by using the method of Budai et al. Finally, the image was projected on to the segmented surface using the lens position as the camera center. In tumor affected eyes, the manually segmented tumors were used instead of the optic disk and macula for the registration. Results In all of the 12 MRI volumes that were tested the 24 eyes were found correctly, including healthy and pathological cases. In healthy eyes the optic nerve head was found in all of the tested eyes with an error of 1.08 +/- 0.37mm. A successful registration can be seen in figure 1. Conclusions The presented method is a step toward automatic fusion of modalities in ophthalmology. The combination enhances the MRI volume with higher resolution from the color fundus on the retina. Tumor treatment planning is improved by avoiding critical structures and disease progression monitoring is made easier.

Explication as a Method of Conceptual Re-engineering

Taking Carnap’s classic exposition as a starting point, this paper develops a pragmatic account of the method of explication, defends it against a range of challenges and proposes a detailed recipe for the practice of explicating. It is then argued that confusions are involved in characterizing explications as definitions, and in advocating precising definitions as an alternative to explications. Explication is better characterized as conceptual re-engineering for theoretical purposes, in contrast to conceptual re-engineering for other purposes and improving exactness for purely practical reasons. Finally, three limitations which call for further development of the method of explication are discussed.

A Hybrid Multimodal Non-Rigid Registration of MR Images Based on Diffeomorphic Demons

n this paper we present a novel hybrid approach for multimodal medical image registration based on diffeomorphic demons. Diffeomorphic demons have proven to be a robust and efficient way for intensity-based image registration. A very recent extension even allows to use mutual information (MI) as a similarity measure to registration multimodal images. However, due to the intensity correspondence uncertainty existing in some anatomical parts, it is difficult for a purely intensity-based algorithm to solve the registration problem. Therefore, we propose to combine the resulting transformations from both intensity-based and landmark-based methods for multimodal non-rigid registration based on diffeomorphic demons. Several experiments on different types of MR images were conducted, for which we show that a better anatomical correspondence between the images can be obtained using the hybrid approach than using either intensity information or landmarks alone.

Patient preference for surgical method of abdominal aortic aneurysm repair: postal survey

To determine whether men with small abdominal aortic aneurysm have a preference between either endovascular or open aneurysm repair for future treatment.

A simple tool for stereological assessment of digital images: the STEPanizer

STEPanizer is an easy-to-use computer-based software tool for the stereological assessment of digitally captured images from all kinds of microscopical (LM, TEM, LSM) and macroscopical (radiology, tomography) imaging modalities. The program design focuses on providing the user a defined workflow adapted to most basic stereological tasks. The software is compact, that is user friendly without being bulky. STEPanizer comprises the creation of test systems, the appropriate display of digital images with superimposed test systems, a scaling facility, a counting module and an export function for the transfer of results to spreadsheet programs. Here we describe the major workflow of the tool illustrating the application on two examples from transmission electron microscopy and light microscopy, respectively.

A novel isolation method of Brucella species and molecular tracking of Brucella suis biovar 2 in domestic and wild animals

Brucella suis biovar 2 is the most common aetiological agent of porcine brucellosis in Europe. B. suis biovar 2 is considered to have low zoonotic potential, but is a causative agent of reproductive losses in pigs, and it is thus economically important. The multilocus variable-number of tandem repeats genotyping analysis of 16 loci (MLVA-16) has proven to be highly discriminatory and is the most suitable assay for simultaneously identifying B. suis and tracking infections. The aim of this study was to investigate the relatedness between isolates of B. suis biovar 2 obtained during a brucellosis outbreak in domestic pigs and isolates from wild boars and hares collected from proximal or remote geographical areas by MLVA-16. A cluster analysis of the MLVA-16 data revealed that most of the isolates obtained from Switzerland clustered together, with the exception of one isolate. The outbreak isolates constituted a unique subcluster (with a genetic similarity >93.8%) distinct from that of the isolates obtained from wild animals, suggesting that direct transmission of the bacterium from wild boars to domestic pigs did not occur in this outbreak. To obtain a representative number of isolates for MLVA-16, alternative methods of Brucella spp. isolation from tissue samples were compared with conventional direct cultivation on a Brucella-selective agar. We observed an enhanced sensitivity when mechanical homogenisation was followed by host cell lysis prior to cultivation on the Brucella-selective agar. This work demonstrates that MLVA-16 is an excellent tool for both monitoring brucellosis and investigating outbreaks. Additionally, we present efficient alternatives for the isolation of Brucella spp.

Radiological anatomy of the obturator nerve and its articular branches: basis to develop a method of radiofrequency denervation for hip joint pain

OBJECTIVE: A previous study of radiofrequency neurotomy of the articular branches of the obturator nerve for hip joint pain produced modest results. Based on an anatomical and radiological study, we sought to define a potentially more effective radiofrequency method. DESIGN: Ten cadavers were studied, four of them bilaterally. The obturator nerve and its articular branches were marked by wires. Their radiological relationship to the bone structures on fluoroscopy was imaged and analyzed. A magnetic resonance imaging (MRI) study was undertaken on 20 patients to determine the structures that would be encountered by the radiofrequency electrode during different possible percutaneous approaches. RESULTS: The articular branches of the obturator nerve vary in location over a wide area. The previously described method of denervating the hip joint did not take this variation into account. Moreover, it approached the nerves perpendicularly. Because optimal coagulation requires electrodes to lie parallel to the nerves, a perpendicular approach probably produced only a minimal lesion. In addition, MRI demonstrated that a perpendicular approach is likely to puncture femoral vessels. Vessel puncture can be avoided if an oblique pass is used. Such an approach minimizes the angle between the target nerves and the electrode, and increases the likelihood of the nerve being captured by the lesion made. Multiple lesions need to be made in order to accommodate the variability in location of the articular nerves. CONCLUSIONS: The method that we described has the potential to produce complete and reliable nerve coagulation. Moreover, it minimizes the risk of penetrating the great vessels. The efficacy of this approach should be tested in clinical trials.

A comparative study on manual and automatic slice-to-volume registration of CT images

In order to assess the clinical relevance of a slice-to-volume registration algorithm, this technique was compared to manual registration. Reformatted images obtained from a diagnostic CT examination of the lower abdomen were reviewed and manually registered by 41 individuals. The results were refined by the algorithm. Furthermore, a fully automatic registration of the single slices to the whole CT examination, without manual initialization, was also performed. The manual registration error for rotation and translation was found to be 2.7+/-2.8 degrees and 4.0+/-2.5 mm. The automated registration algorithm significantly reduced the registration error to 1.6+/-2.6 degrees and 1.3+/-1.6 mm (p = 0.01). In 3 of 41 (7.3%) registration cases, the automated registration algorithm failed completely. On average, the time required for manual registration was 213+/-197 s; automatic registration took 82+/-15 s. Registration was also performed without any human interaction. The resulting registration error of the algorithm without manual pre-registration was found to be 2.9+/-2.9 degrees and 1.1+/-0.2 mm. Here, a registration took 91+/-6 s, on average. Overall, the automated registration algorithm improved the accuracy of manual registration by 59% in rotation and 325% in translation. The absolute values are well within a clinically relevant range.

Approximating method of frames

In this paper, the well-known method of frames approach to the signal decomposition problem is reformulated as a certain bilevel goal-attainment linear least squares problem. As a consequence, a numerically robust variant of the method, named approximating method of frames, is proposed on the basis of a certain minimal Euclidean norm approximating splitting pseudo-iteration-wise method.