F Güttler

Forensic Odontology: Automatic Identification of Persons Comparing Antemortem and Postmortem Panoramic Radiographs Using Computer Vision

PURPOSE  In forensic odontology the comparison between antemortem and postmortem panoramic radiographs (PRs) is a reliable method for person identification. The purpose of this study was to improve and automate identification of unknown people by comparison between antemortem and postmortem PR using computer vision. MATERIALS AND METHODS  The study includes 43 467 PRs from 24 545 patients (46 % females/54 % males). All PRs were filtered and evaluated with Matlab R2014b including the toolboxes image processing and computer vision system. The matching process used the SURF feature to find the corresponding points between two PRs (unknown person and database entry) out of the whole database. RESULTS  From 40 randomly selected persons, 34 persons (85 %) could be reliably identified by corresponding PR matching points between an already existing scan in the database and the most recent PR. The systematic matching yielded a maximum of 259 points for a successful identification between two different PRs of the same person and a maximum of 12 corresponding matching points for other non-identical persons in the database. Hence 12 matching points are the threshold for reliable assignment. CONCLUSION  Operating with an automatic PR system and computer vision could be a successful and reliable tool for identification purposes. The applied method distinguishes itself by virtue of its fast and reliable identification of persons by PR. This Identification method is suitable even if dental characteristics were removed or added in the past. The system seems to be robust for large amounts of data. KEY POINTS   · Computer vision allows an automated antemortem and postmortem comparison of panoramic radiographs (PRs) for person identification.. · The present method is able to find identical matching partners among huge datasets (big data) in a short computing time.. · The identification method is suitable even if dental characteristics were removed or added.. CITATION FORMAT · Heinrich A, Güttler F, Wendt S et al. Forensic Odontology: Automatic Identification of Persons Comparing Antemortem and Postmortem Panoramic Radiographs Using Computer Vision. Fortschr Röntgenstr 2018; 190: 1152 - 1158.

Fully automatic CT-histogram-based fat estimation in dead bodies

Post-mortem body cooling is the foundation of temperature-based death time estimations (TDE) in homicide cases. Forensic science generally provides two types of p.m. body cooling models, the phenomenological and the physical models. Since both of them have to implement important individual parameters like the quantity of abdominal fat explicitly or implicitly, a more exact quantification and localization of abdominal fat is a desideratum in TDE. Particularly for the physical models, a better knowledge of the abdominal fat distribution could lead to relevant improvements in TDEs. Modern imaging methods in medicine like computed tomography (CT) are opening up the possibility to register the quantity and spatial distribution of body fat in individual cases with unprecedented precision. Since a CT-scan of an individual’s abdominal region can comprise 1000 slices as an order of magnitude, it is evident that their evaluation for body fat quantification and localization needs fully automated algorithms. The paper at hand describes the development and validation of such an algorithm called “CT-histogram-based fat estimation and quasi-segmentation” (CFES). The approach can be characterized as a weighted least squares method dealing with the gray value histogram of single CT-slices only. It does not require any anatomical a priori information nor does it perform time-consuming feature detection on the CT-images. The processing result consists in numbers quantifying the amount of abdominal body fat and of muscle-, organ-, and connective tissue. As a by-product, CFES generates a quasi-segmentation of the slices processed differentiating fat from muscle-, organ-, and connective tissue. The tool is validated on synthetic data and on CT-data of a special phantom. It was also applied on a CT-scan of a dead body, where it produced anatomically plausible results.

Introduction of an open source middleware for automatic FOV adjustment in interactive MRI according to a medical tracking-system

In real-time MRI-guided interventions and surgery [1], the field-of-view (FOV) of interactive sequences needs to be permanently changed according to the instruments movement. Dynamic tracking [2] allows the automatic adaption of the FOV to the instruments location acquired by a medical tracking-system. To accomplish manufacturer independent use of dynamic tracking, a middleware was developed allowing the use of various MRIs and tracking-systems.