Practical Object-Oriented Back-in-Time Debugging

Back-in-time debuggers are extremely useful tools for identifying the causes of bugs, as they allow us to inspect the past states of objects no longer present in the current execution stack. Unfortunately the "omniscient" approaches that try to remember all previous states are impractical because they either consume too much space or they are far too slow. Several approaches rely on heuristics to limit these penalties, but they ultimately end up throwing out too much relevant information. In this paper we propose a practical approach to back-in-time debugging that attempts to keep track of only the relevant past data. In contrast to other approaches, we keep object history information together with the regular objects in the application memory. Although seemingly counter-intuitive, this approach has the effect that past data that is not reachable from current application objects (and hence, no longer relevant) is automatically garbage collected. In this paper we describe the technical details of our approach, and we present benchmarks that demonstrate that memory consumption stays within practical bounds. Furthermore since our approach works at the virtual machine level, the performance penalty is significantly better than with other approaches.

Haptics in forensics: the possibilities and advantages in using the haptic device for reconstruction approaches in forensic science

Non-invasive documentation methods such as surface scanning and radiological imaging are gaining in importance in the forensic field. These three-dimensional technologies provide digital 3D data, which are processed and handled in the computer. However, the sense of touch gets lost using the virtual approach. The haptic device enables the use of the sense of touch to handle and feel digital 3D data. The multifunctional application of a haptic device for forensic approaches is evaluated and illustrated in three different cases: the representation of bone fractures of the lower extremities, by traffic accidents, in a non-invasive manner; the comparison of bone injuries with the presumed injury-inflicting instrument; and in a gunshot case, the identification of the gun by the muzzle imprint, and the reconstruction of the holding position of the gun. The 3D models of the bones are generated from the Computed Tomography (CT) images. The 3D models of the exterior injuries, the injury-inflicting tools and the bone injuries, where a higher resolution is necessary, are created by the optical surface scan. The haptic device is used in combination with the software FreeForm Modelling Plus for touching the surface of the 3D models to feel the minute injuries and the surface of tools, to reposition displaced bone parts and to compare an injury-causing instrument with an injury. The repositioning of 3D models in a reconstruction is easier, faster and more precisely executed by means of using the sense of touch and with the user-friendly movement in the 3D space. For representation purposes, the fracture lines of bones are coloured. This work demonstrates that the haptic device is a suitable and efficient application in forensic science. The haptic device offers a new way in the handling of digital data in the virtual 3D space.

Radiation dose reduction in computer assisted navigation for functional endoscopic sinus surgery--cadaver head experiments and clinical implementation

Computed tomography based navigation for endoscopic sinus surgery is inflationary used despite of major public concern about iatrogenic radiation induced cancer risk. Studies on dose reduction for CAS-CT are almost nonexistent. We validate the use of radiation dose reduced CAS-CT for clinically applied surface registration.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Lessons in Software Evolution Learned by Listening to Smalltalk

The biggest challenge facing software developers today is how to gracefully evolve complex software systems in the face of changing requirements. We clearly need software systems to be more dynamic, compositional and model-centric, but instead we continue to build systems that are static, baroque and inflexible. How can we better build change-enabled systems in the future? To answer this question, we propose to look back to one of the most successful systems to support change, namely Smalltalk. We briefly introduce Smalltalk with a few simple examples, and draw some lessons for software evolution. Smalltalk's simplicity, its reflective design, and its highly dynamic nature all go a long way towards enabling change in Smalltalk applications. We then illustrate how these lessons work in practice by reviewing a number of research projects that support software evolution by exploiting Smalltalk's design. We conclude by summarizing open issues and challenges for change-enabled systems of the future.

Steerable intravitreal inserts for drug delivery: in vitro and ex vivo mobility experiments

The progress of wet age-related macular degeneration can now be controlled by intravitreal drug injection. This approach requires repeated injections, which could be avoided by delivering the drug to the retina. Intraocular implants are a promising solution for drug delivery near the retina. Currently, their accurate placement is challenging, and they can only be removed after a vitrectomy. In this paper, we introduce an approach for minimally invasive retinal drug delivery using magnetic intraocular inserts. We briefly discuss the electromagnetic-control system for magnetic implants and then focus on evaluating their ability to move in the vitreous humor. The mobility of magnetic intraocular implants is estimated in vitro with synthesized vitreous humors, and ex vivo with experiments on cadaver porcine eyes. Preliminary results show that with such magnetic implants a vitrectomy can be avoided.

Endoscopic Image Overlay for the Targeting of Hidden Anatomy in Laparoscopic Visceral Surgery

Limitations associated with the visual information provided to surgeons during laparoscopic surgery increases the difficulty of procedures and thus, reduces clinical indications and increases training time. This work presents a novel augmented reality visualization approach that aims to improve visual data supplied for the targeting of non visible anatomical structures in laparoscopic visceral surgery. The approach aims to facilitate the localisation of hidden structures with minimal damage to surrounding structures and with minimal training requirements. The proposed augmented reality visualization approach incorporates endoscopic images overlaid with virtual 3D models of underlying critical structures in addition to targeting and depth information pertaining to targeted structures. Image overlay was achieved through the implementation of camera calibration techniques and integration of the optically tracked endoscope into an existing image guidance system for liver surgery. The approach was validated in accuracy, clinical integration and targeting experiments. Accuracy of the overlay was found to have a mean value of 3.5 mm ± 1.9 mm and 92.7% of targets within a liver phantom were successfully located laparoscopically by non trained subjects using the approach.