The impact of anatomy variation on temperature based time of death estimation.

Temperature-based time of death estimation using simulation methods such as the finite element method promise higher accuracy and broader applicability in nonstandard cooling scenarios than established phenomenological methods. Their accuracy depends crucially on the simulation model to capture the actual situation, which in turn hinges on the representation of the corpse's anatomy in form of computational meshes as well as on the thermodynamic parameters. While inaccuracies in anatomy representation due to coarse mesh resolution are known to have a minor impact on the estimated time of death, the sensitivity with respect to larger differences in the anatomy has so far not been studied. We assess this sensitivity by comparing four independently generated and vastly different anatomical models in terms of the estimated time of death in an identical cooling scenario. In order to isolate the impact of shape variation, the models are scaled to a reference size, and the possible impact of measurement location variation is excluded explicitly by finding measurement locations leading to minimum deviations. The thus obtained lower bound on the impact of anatomy on the estimated time of death shows, that anatomy variations lead to deviations of at least 5-10%.

CT-based thermometry with virtual monoenergetic images by dual-energy of fat, muscle and bone using FBP, iterative and deep learning-based reconstruction.

OBJECTIVES: The aim of this study was to evaluate the sensitivity of CT-based thermometry for clinical applications regarding a three-component tissue phantom of fat, muscle and bone. Virtual monoenergetic images (VMI) by dual-energy measurements and conventional polychromatic 120-kVp images with modern reconstruction algorithms adaptive statistical iterative reconstruction-Volume (ASIR-V) and deep learning image reconstruction (DLIR) were compared. METHODS: A temperature-regulating water circuit system was developed for the systematic evaluation of the correlation between temperature and Hounsfield units (HU). The measurements were performed on a Revolution CT with gemstone spectral imaging technology (GSI). Complementary measurements were performed without GSI (voltage 120 kVp, current 130-545 mA). The measured object was a tissue equivalent phantom in a temperature range of 18 to 50°C. The evaluation was carried out for VMI at 40 to 140 keV and polychromatic 120-kVp images. RESULTS: The regression analysis showed a significant inverse linear dependency between temperature and average HU regardless of ASIR-V and DLIR. VMI show a higher temperature sensitivity compared to polychromatic images. The temperature sensitivities were 1.25 HU/°C (120 kVp) and 1.35 HU/°C (VMI at 140 keV) for fat, 0.38 HU/°C (120 kVp) and 0.47 HU/°C (VMI at 40 keV) for muscle and 1.15 HU/°C (120 kVp) and 3.58 HU/°C (VMI at 50 keV) for bone. CONCLUSIONS: Dual-energy with VMI enables a higher temperature sensitivity for fat, muscle and bone. The reconstruction with ASIR-V and DLIR has no significant influence on CT-based thermometry, which opens up the potential of drastic dose reductions. KEY POINTS: • Virtual monoenergetic images (VMI) enable a higher temperature sensitivity for fat (8%), muscle (24%) and bone (211%) compared to conventional polychromatic 120-kVp images. • With VMI, there are parameters, e.g. monoenergy and reconstruction kernel, to modulate the temperature sensitivity. In contrast, there are no parameters to influence the temperature sensitivity for conventional polychromatic 120-kVp images. • The application of adaptive statistical iterative reconstruction-Volume (ASIR-V) and deep learning-based image reconstruction (DLIR) has no effect on CT-based thermometry, opening up the potential of drastic dose reductions in clinical applications.

Fractures and skin lesions in pediatric abusive head trauma: a forensic multi-center study.

Abusive head trauma (AHT) and its most common variant, the shaken baby syndrome (SBS), are predominantly characterized by central nervous system-associated lesions. Relatively little data are available on the value of skeletal and skin injuries for the diagnosis of SBS or AHT. Thus, the present study retrospectively investigated 72 cases of living children diagnosed with the explicit diagnosis of SBS during medico-legal examinations at three German university institutes of legal medicine. The risk of circular reasoning was reduced by the presence of 15 cases with confession by perpetrators. Accordingly, the comparison with the 57 non-confession cases yielded no significant differences. Skeletal survey by conventional projection radiography, often incomplete, was found to be performed in 78% of the cases only. Fractures were found in 32% of the cases. The skull (43%) and ribs (48%) were affected most frequently; only 8% of the cases showed classic metaphyseal lesions. In 48% of the cases, healing fractures were present. Skin lesions (hematomas and abrasions) were found in 53% of the cases with the face (76%), scalp (26%), and trunk (50%) being the major sites. In 48% of the cases, healing skin lesions were observed. Nearly 80% of the cases with fractures also showed skin lesions. The data prove that SBS is frequently accompanied by other forms of physical abuse. Therefore, skeletal survey is indispensable and should always be done completely and according to existing imaging guidelines if child abuse is suspected.

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.

Automatic CT-based finite element model generation for temperature-based death time estimation: feasibility study and sensitivity analysis.

Temperature-based death time estimation is based either on simple phenomenological models of corpse cooling or on detailed physical heat transfer models. The latter are much more complex but allow a higher accuracy of death time estimation, as in principle, all relevant cooling mechanisms can be taken into account.Here, a complete workflow for finite element-based cooling simulation is presented. The following steps are demonstrated on a CT phantom: Computer tomography (CT) scan Segmentation of the CT images for thermodynamically relevant features of individual geometries and compilation in a geometric computer-aided design (CAD) model Conversion of the segmentation result into a finite element (FE) simulation model Computation of the model cooling curve (MOD) Calculation of the cooling time (CTE) For the first time in FE-based cooling time estimation, the steps from the CT image over segmentation to FE model generation are performed semi-automatically. The cooling time calculation results are compared to cooling measurements performed on the phantoms under controlled conditions. In this context, the method is validated using a CT phantom. Some of the phantoms' thermodynamic material parameters had to be determined via independent experiments.Moreover, the impact of geometry and material parameter uncertainties on the estimated cooling time is investigated by a sensitivity analysis.

Biomechanical assessment of the injury risk of stomping.

Forensic case work as well as literature shows that severe head injuries, e.g., with basilar fractures and cerebral hemorrhages due to stomps can be seen; however, there is no data basis concerning contact forces and potential influencing factors. The objective of this work was to generate a data basis of contact forces in stomping by performing experimental measurements and subsequent statistical analyses. Fifty-five volunteers participated in the present study. Each participant performed several stomps onto force plates with sturdy/soft footwear as well as with/without an elastic layer imitating the scalp. Ground reaction forces induced by jumps were also measured for sturdy and soft footwear. The results show statistically significant dependencies between maximum ground reaction forces and body weight and body height. A statistically significant influence of footwear on stomping force could only be found in tests with an elastic layer and in the jumping setup. Mean maximum stomping forces for the female volunteers were between 4694 and 5970 N; male volunteers were able to produce mean peak stomping forces between 8494 and 9016 N. Jumping forces were approximately twice the stomping forces for both male and female test persons. Regardless of footwear and gender, it can be claimed that a forceful stomp or jump to someone's head supported on the ground can cause facial and skull fractures. Thus, forceful stomps or jumps to someone's head can cause potential fatal injuries independent of footwear, gender, or fitness level.

Quality measures for fully automatic CT histogram-based fat estimation on a corpse sample.

In a previous article a new algorithm for fully automatic 'CT histogram based Fat Estimation and quasi-Segmentation' (CFES) was validated on synthetic data, on a special CT phantom, and tested on one corpse. Usage of said data in FE-modelling for temperature-based death time estimation is the investigation's number one long-term goal. The article presents CFES's results on a human corpse sample of size R = 32, evaluating three different performance measures: the τ-value, measuring the ability to differentiate fat from muscle, the anatomical fat-muscle misclassification rate D, and the weighted distance S between the empirical and the theoretical grey-scale value histogram. CFES-performance on the sample was: D = 3.6% for weight exponent α = 1, slightly higher for α ≥ 2 and much higher for α ≤ 0. Investigating τ, S and D on the sample revealed some unexpected results: While large values of τ imply small D-values, rising S implies falling D and there is a positive linear relationship between τ and S. The latter two findings seem to be counter-intuitive. Our Monte Carlo analysis detected a general umbrella type relation between τ and S, which seems to stem from a pivotal problem in fitting Normal mixture distributions.

Automatic human identification based on dental X-ray radiographs using computer vision.

A person may be identified by comparison between ante- and post-mortem dental panoramic radiographs (DPR). However, it is difficult to find reference material if the person is unknown. This is often the case when victims of crime or mass disaster are found. Computer vision can be a helpful solution to automate the finding of reference material in a large database of images. The purpose of the present study was to improve the automated identification of unknown individuals by comparison of ante- and post-mortem DPR using computer vision. The study includes 61,545 DPRs from 33,206 patients, acquired between October 2006 and June 2018. The matching process is based on the Speeded Up Robust Features (SURF) algorithm to find unique corresponding points between two DPRs (unknown person and database entry). The number of matching points found is an indicator for identification. All 43 individuals (100%) were successfully identified by comparison with the content of the feature database. The experimental setup was designed to identify unknown persons based on their DPR using an automatic algorithm system. The proposed tool is able to filter large databases with many entries of potentially matching partners. This identification method is suitable even if dental characteristics were removed or added in the past.

Temperature-based death time estimation in near equilibrium: Asymptotic confidence interval estimation.

Temperature based death time estimation (TDE) is severely limited in situations where body core temperature has almost decreased to ambient temperature. The TDE method of Marshall/Hoare and Henßge (MHH) defines a lower bound TK for body core temperature below which the time p.m. should be stated to be >10h only. A recent study (Potente et al., 2017 [10]) established a new method, called variance-bias-tradeoff (VBT) complementing MHH in constructing a right-side-half-infinite 97.5%-confidence interval for such 'near equilibrium'-situations. It seemingly proved the validity for all body core temperatures T

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.