Cost-effective 3D documentation device in forensic medicine.

3D documentation in forensics and forensic medicine is being introduced more frequently in various institutes around the world. However, several institutes lack capacity in finances as well as staff to perform 3D documentations regularly. This technical paper aims to present a 3D documentation device that is low cost and easy to use and is a viable entry level solution for forensic medical departments. For this the small single-board computer Raspberry Pi 4 was used in conjunction with its high quality (HQ) camera module to create the 3DLamp - a flexible, low cost and easy to use documentation device. Besides a detailed description of the device this paper also presents four case examples where a 3D documentation was performed and analyses the acquired data and the created 3D models. It was found that the device returns feasible 3D models that appear usable for forensic 3D reconstructions.

Augmented reality in forensics and forensic medicine - Current status and future prospects.

Forensic investigations require a vast variety of knowledge and expertise of each specialist involved. With the increase in digitization and advanced technical possibilities, the traditional use of a computer with a screen for visualization and a mouse and keyboard for interactions has limitations, especially when visualizing the content in relation to the real world. Augmented reality (AR) can be used in such instances to support investigators in various tasks at the scene as well as later in the investigation process. In this article, we present current applications of AR in forensics and forensic medicine, the technological basics of AR, and the advantages that AR brings for forensic investigations. Furthermore, we will have a brief look at other fields of application and at future developments of AR in forensics.

Automated wound segmentation and classification of seven common injuries in forensic medicine.

In forensic medical investigations, physical injuries are documented with photographs accompanied by written reports. Automatic segmentation and classification of wounds on these photographs could provide forensic pathologists with a tool to improve the assessment of injuries and accelerate the reporting process. In this pilot study, we trained and compared several preexisting deep learning architectures for image segmentation and wound classification on forensically relevant photographs in our database. The best scores were a mean pixel accuracy of 69.4% and a mean intersection over union (IoU) of 48.6% when evaluating the trained models on our test set. The models had difficulty distinguishing the background from wounded areas. As an example, image pixels showing subcutaneous hematomas or skin abrasions were assigned to the background class in 31% of cases. Stab wounds, on the other hand, were reliably classified with a pixel accuracy of 93%. These results can be partially attributed to undefined wound boundaries for some types of injuries, such as subcutaneous hematoma. However, despite the large class imbalance, we demonstrate that the best trained models could reliably distinguish among seven of the most common wounds encountered in forensic medical investigations.

Technical note: Semiautomated targeted postmortem computed tomography angiography of the pulmonary arteries using a robotic system.

INTRODUCTION: To better depict vascular lesions on postmortem computed tomography (PMCT), whole-body postmortem computed tomography angiography (PMCTA) can be used in forensic diagnostics. Targeted angiography, in which only a specific vessel is filled with contrast agent, might help in cases of traumatic changes that render whole-body PMCTA impossible. Moreover, in targeted PMCTA, the contrast agent does not affect the haptics of any other organs. In this article, we describe automated, CT-guided targeted angiography of the pulmonary artery (PA) using the Virtobot system. MATERIAL AND METHODS: Our study group consisted of 8 deceased persons (3 males, 5 females). We first performed an unenhanced CT scan and used the data obtained to plan the needle trajectories with the Virtobot planning software. Then, the needle was fully automatically placed by the Virtobot system. Subsequently, 50 ml of contrast agent was injected manually, and the CT scan was repeated (targeted PMCTA). RESULTS AND DISCUSSION: We tested a new method for performing semiautomated targeted postmortem angiography of the PAs using a robotic needle placement system (Virtobot). In 6 out of our 8 cases, the injection of contrast agent in the PA was successful. In five of the six successful cases, there was reflux of contrast agent to some extent, but the reflux did not affect the readout. In general, the procedure was easy to plan based on a PMCT data set, and the pulmonary trunk was easy to reach with a robotic needle placement system.

Identification parade in immersive virtual reality - A technical setup.

Virtual Reality (VR) has sparked interest within the forensic community, where it is currently used for training purposes and in variety of forensic scenarios. In combination with efficient and user friendly full body 3-Dimensional (3D) documentation methods, VR visualisations present a viable tool for suspect witness identification. The well-known procedure of placing several persons in a room with a one-way-mirror, along with a witness on the other side of the mirror has practical disadvantages. The primary concern implicates the witness(s) and person(s) of interest coming face-to-face prior to the line-up, combined with finding sufficient persons to include within the line-up. Although image identification using printed paper partially resolved this problem, features such as body stature also marks an issue for the recognition and identification process. To test whether VR provides the technical capabilities to perform an identification parade, a total of 15 subjects were 3D documented using the multi-camera device "Photobox". From this group, one of the documented persons then interrupted a lecture, where consequently, the students were asked afterwards to identify the same person in VR and paper identification sets. It was found that the participating students were able to identify the "suspect" in both datasets. The results imply that VR technology allow users to identify persons. However, as this is a preliminary study the similarity problem was not analysed in this paper and requires further investigation to demonstrate the robustness of this approach.

Forensic examination of living persons in 3D models.

Physical injuries caused by interpersonal violence or accidents are usually documented with photographs. In addition to standard injury photography using 2D photographs, the Institute *INSTITUT NAME BLINDED FOR REVIEW* uses a Botspot Botscan ® multi-camera device (Photobox; Aniwaa Ltd, Berlin, Germany) that allows for 3D documentation of a subject. The Photobox contains 70 cameras positioned at different heights looking at a central platform. Within a fraction of a second, all cameras are activated and acquire the necessary images for 3D documentation. In previous studies by Michienzi et al. (2018), the geometric correctness of 3D documented injuries was analyzed. While their work concentrated solely on artificial injuries and their dimensions, the work presented in this study analyzes whether the Photobox allows for accurate medical interpretation of injuries, by forensic pathologists. To perform this analysis, 40 datasets of a variety of real cases were processed to 3D models. The created 3D models were then examined by forensic pathologists on 2D computer screens, and the findings were compared with the original reports. While the aim of this work was to assess whether examinations based on a 3D model allows comparable results to immediate examinations of the subject, the results showed that examinations based on a 3D model are 85% accurate when comparing with physical examinations. This indicates that 3D models allow for reasonably accurate interpretation, and it is possible that accuracy might increase with improved equipment and better trained personnel.

RiFNet: Automated rib fracture detection in postmortem computed tomography.

Imaging techniques are widely used for medical diagnostics. In some cases, a lack of medical practitioners who can manually analyze the images can lead to a bottleneck. Consequently, we developed a custom-made convolutional neural network (RiFNet = Rib Fracture Network) that can detect rib fractures in postmortem computed tomography. In a retrospective cohort study, we retrieved PMCT data from 195 postmortem cases with rib fractures from July 2017 to April 2018 from our database. The computed tomography data were prepared using a plugin in the commercial imaging software Syngo.via whereby the rib cage was unfolded on a single-in-plane image reformation. Out of the 195 cases, a total of 585 images were extracted and divided into two groups labeled "with" and "without" fractures. These two groups were subsequently divided into training, validation, and test datasets to assess the performance of RiFNet. In addition, we explored the possibility of applying transfer learning techniques on our dataset by choosing two independent noncommercial off-the-shelf convolutional neural network architectures (ResNet50 V2 and Inception V3) and compared the performances of those two with RiFNet. When using pre-trained convolutional neural networks, we achieved an F1 score of 0.64 with Inception V3 and an F1 score of 0.61 with ResNet50 V2. We obtained an average F1 score of 0.91 ± 0.04 with RiFNet. RiFNet is efficient in detecting rib fractures on postmortem computed tomography. Transfer learning techniques are not necessarily well adapted to make classifications in postmortem computed tomography.

The forensic holodeck - Recommendations after 8 years of experience for additional equipment to document VR applications.

The forensic holodeck was first introduced in 2013, using the first upcoming commercially available virtual reality gaming headsets to visualize forensic 3D reconstructions. Following the publication of this development virtual reality was introduced in case work in a variety of different ways. After 8 years of using virtual reality in a professional forensic capacity this professional practice report will show, which equipment is necessary in addition to a virtual reality setup. This mostly includes audio-visual and broadcasting technology for complete documentation of the application of virtual reality, but also some other IT equipment, which should be available for as low as 20'000 US$. Guidelines, hints and tips regarding equipment acquisition, setup and use will be provided and discussed.

Comparison of superficial wound documentation using 2D forensic photography, 3D photogrammetry, Botscan© and VR with real-life examination.

Evidence acquisition, interpretation and preservation are essential parts of forensic case work that make a standardized documentation process fundamental. The most commonly used method for the documentation and interpretation of superficial wounds is a combination of two modalities: two-dimensional (2D) photography for evidence preservation and real-life examination for wound analysis. As technologies continue to develop, 2D photography is being enhanced with three-dimensional (3D) documentation technology. In our study, we compared the real-life examination of superficial wounds using four different technical documentation and visualization methods.To test the different methods, a mannequin was equipped with several injury stickers, and then the different methods were applied. A total of 42 artificial injury stickers were documented in regard to orientation, form, color, size, wound borders, wound corners and suspected mechanism of injury for the injury mechanism. As the gold standard, superficial wounds were visually examined by two board-certified forensic pathologists directly on the mannequin. These results were compared to an examination using standard 2D forensic photography; 2D photography using the multicamera system Botscan©, which included predefined viewing positions all around the body; and 3D photogrammetric reconstruction based on images visualized both on screen and in a virtual reality (VR) using a head-mounted display (HMD).The results of the gold standard examination showed that the two forensic pathologists had an inter-reader agreement ranging from 69% for the orientation and 11% for the size of the wounds. A substantial portion of the direct visual documentation showed only a partial overlap, especially for the items of size and color, thereby prohibiting the statistical comparison of these two items. A forest plot analysis of the remaining six items showed no significant difference between the methods. We found that among the forensic pathologists, there was high variability regarding the vocabulary used for the description of wound morphology, which complicated the exact comparison of the two documentations of the same wound.There were no significant differences for any of the four methods compared to the gold standard, thereby challenging the role of real-life examination and 2D photography as the most reliable documentation approaches. Further studies with real injuries are necessary to support our evaluation that technical examination methods involving multicamera systems and 3D visualization for whole-body examination might be a valid alternative in future forensic documentation.

A review of visualization techniques of post-mortem computed tomography data for forensic death investigations.

Postmortem computed tomography (PMCT) is a standard image modality used in forensic death investigations. Case- and audience-specific visualizations are vital for identifying relevant findings and communicating them appropriately. Different data types and visualization methods exist in 2D and 3D, and all of these types have specific applications. 2D visualizations are more suited for the radiological assessment of PMCT data because they allow the depiction of subtle details. 3D visualizations are better suited for creating visualizations for medical laypersons, such as state attorneys, because they maintain the anatomical context. Visualizations can be refined by using additional techniques, such as annotation or layering. Specialized methods such as 3D printing and virtual and augmented reality often require data conversion. The resulting data can also be used to combine PMCT data with other 3D data such as crime scene laser scans to create crime scene reconstructions. Knowledge of these techniques is essential for the successful handling of PMCT data in a forensic setting. In this review, we present an overview of current visualization techniques for PMCT.

An algorithm for automatically generating gas, bone and foreign body visualizations from postmortem computed tomography data.

Post mortem computed tomography (PMCT) can aid in localizing foreign bodies, bone fractures, and gas accumulations. The visualization of these findings play an important role in the communication of radiological findings. In this article, we present an algorithm for automated visualization of gas distributions on PMCT image data of the thorax and abdomen. The algorithm uses a combination of region growing segmentation and layering of different visualization methods to automatically generate overview images that depict radiopaque foreign bodies, bones and gas distributions in one image. The presented method was tested on 955 PMCT scans of the thorax and abdomen. The algorithm managed to generate useful images for all cases, visualizing foreign bodies as well as gas distribution. The most interesting cases are presented in this article. While this type of visualization cannot replace a real radiological analysis of the image data, it can provide a quick overview for briefings and image reports.

Potential use of deep learning techniques for postmortem imaging.

The use of postmortem computed tomography in forensic medicine, in addition to conventional autopsy, is now a standard procedure in several countries. However, the large number of cases, the large amount of data, and the lack of postmortem radiology experts have pushed researchers to develop solutions that are able to automate diagnosis by applying deep learning techniques to postmortem computed tomography images. While deep learning techniques require a good understanding of image analysis and mathematical optimization, the goal of this review was to provide to the community of postmortem radiology experts the key concepts needed to assess the potential of such techniques and how they could impact their work.

Clinical forensic height measurements on injured people using a multi camera device for 3D documentation.

Documenting the existence, size, position and shape of injuries is an important part of medical forensic examinations. In the photography of an injury, the documentation is limited to an approximation of size and position of the injury based on a ruler included in the image. The documentation of injuries can be improved with photogrammetry, which allows the creation of scaled 3D models of an injury that can be used to not only document and visualize the injury but also to match the injury with an injury-causing object. In this paper, the multicamera device "Botscan" was used to perform 3D whole-body documentation and measure the positions of injuries. A major advantage of 3D whole-body documentation compared to photography is that the former can be performed at a later stage of the investigation. This makes the whole-body 3D documentation of injuries an important tool for re-examination.

A toolbox for the rapid prototyping of crime scene reconstructions in virtual reality.

Virtual reality is recently finding its way in forensic work. The required 3D data is nowadays a standard dataset available in many cases, from homicide to traffic collisions, including not only data from the scene but also of weaponry and involved persons. Current investigations use these 3D data to replicated the incident and as discussion base for forensic personal. However, modifying the scene on a 2D viewport is often cumbersome due to the loss of the third dimension. Also to perform the modifications on the scene a 3D operator is often required. Virtual reality might improve this step by its easy use and by visualising the third dimension. This publication presents a variety of tools which can be used in forensic investigations. Additionally to the tools, examples of forensic use of these tools will be presented, showing that already a small number of tools support a variety of forensic applications.

3D mug shot-3D head models from photogrammetry for forensic identification.

No human face is like another, not even in monozygotic twins, which makes the face one of the most individualizing characteristic. It is for this reason that the human face is commonly used for identification purposes and police officers take portrait photographs of arrested persons, so-called mug shots. The disadvantage of these 2D mug shots is that the perspective, in which they are taken (usually frontal and lateral-right, left or both), cannot be changed after acquisition, thus limiting a potential comparison between a mug shot and surveillance footage or other visual recordings. Documenting a face in 3D would reduce this problem as it allows adjusting the perspective of the face for image comparisons depending on the needs of the investigator. We have developed a 3D mug shot system containing 26 digital single-lens reflex cameras arranged semi-circularly in a 200° arc with a 1.46 m radius around a height-adjustable chair. We generated photogrammetric models of a test person's face captured by the mug shot system using three different focal lengths settings as well as 3D models of the same face with GOM Atos Triple Scan and Artec Space Spider. The 3D models were then analysed regarding the visibility of detailed morphological features in different regions of the face compared to 2D mug shots. Our results showed that our 3D mug shot system with its photogrammetric documentation generates 3D models with comparable surface quality to Artec-generated models, or even better quality, compared to GOM-generated models. The results of the morphological assessment were affected by the focal length and availability of texture information. In conclusion, the 3D mug shot system is a fast and efficient tool to generate 3D models of the face and may be used in addition to 2D photographs for the purpose of visual forensic identification based on images.

Using virtual reality for forensic examinations of injuries.

The ability to accurately determine injury dimensions is an essential property of forensic documentation. The current standard for injury documentation is photography using a scale to approximate the injury dimensions in the image. The technical qualities of the photograph, such as orthogonality, depth of the field and sharpness of the desired area, are vital to obtaining a correct measurement. Adequate training of the forensic staff can reduce technical errors; nonetheless, there will always be some loss of information when visualizing an injury as a three-dimensional (3D) object on a two-dimensional (2D) photograph. The shortcomings of 2D photographs can be resolved by using 3D photogrammetry, which allows 3D documentation of persons and their injuries. A series of photographs has to be acquired and processed in photogrammetric software to create a photorealistic 3D model. In a prior study, a mannequin equipped with wound tattoos of known dimensions was documented with 3D photogrammetry using a multi-camera device. On the created 3D model, the dimensions of the injuries were then measured and compared to the dimensions approximated from standard forensic photographs. The results showed that the photogrammetric measurements in 3D are more accurate than the approximations performed with standard forensic photographs. In this subsequent study, the created 3D model was visualized and surveyed in virtual reality (VR), and the results were compared to the previous study. Our goal was to establish how accurately injuries can be measured in VR compared to the standard forensic photo documentation and photogrammetric method that is used on computer screens. We found that the measurements in VR are more accurate than the approximations from forensic photo documentation, but slightly less accurate than the photogrammetric measurements performed on a computer screen in dedicated software. In conclusion, photogrammetric software and virtual reality tools can both be used to make accurate size measurements of forensics-relevant injuries. Furthermore, 3D models can be visualized in varying ways allowing a much better understanding and review of injuries, even after the injury has healed.

Applying virtual reality in forensics - a virtual scene walkthrough.

A major task of forensic investigations is the documentation and interpretation of evidence to reconstruct a forensically relevant incident. To accomplish this task, a scene is documented not only with photographs but also with 3D documentation technologies. The resulting 3D data are used for 3D visualization and to perform 3D reconstructions. In this article, we present an approach for using forensic 3D data in conjunction with virtual reality to perform scene walkthroughs in the context of witness or suspect interrogations. The aim is to provide a method for scene visits showing the original scene even years after the incident. These scene walkthroughs in VR can be reproduced and allow to see through the eyes of a witness by recording their behavior and actions. These recordings allow subsequent examinations and reconstruction to support the investigation and scene understanding and can be used as evidence in court.

Comparison of forensic photo-documentation to a photogrammetric solution using the multi-camera system "Botscan".

As forensic science technologies progress, digital photography has become outdated for certain documentations that require exact measurements. Recording three-dimensional objects on a two-dimensional photograph leads to a potential loss of relevant information. Photogrammetry has been utilized to record persons, objects or crime scenes and prevents this loss. Photogrammetry enables accurate documentation and visualization of events or matching of injuries and injury-causing instruments. To reduce inaccuracies during photogrammetric recording, a multi camera device, Botscan by Botspot, can be used to record living persons in three-dimensional space (3D). The device can record a full body in a fraction of a second, which leads to a significant reduction of inaccuracies due to movement. Photogrammetric measurements were compared with measurements from forensic photographs to evaluate the applicability of this device for medical forensic documentation of injuries. For this purpose, a mannequin fitted with different types of artificial injuries was used as an example. The results showed that the photogrammetric measurements obtained using the software Agisoft PhotoScan were more accurate than the measurements from the forensic photographs.

Differentiation of dental restorative materials combining energy-dispersive X-ray fluorescence spectroscopy and post-mortem CT.

Today, post-mortem computed tomography (CT) is routinely used for forensic identification. Mobile energy-dispersive X-ray fluorescence (EDXRF) spectroscopy of a dentition is a method of identification that has the potential to be easier and cheaper than CT, although it cannot be used with every dentition. In challenging cases, combining both techniques could facilitate the process of identification and prove to be advantageous over chemical analyses. Nine dental restorative material brands were analyzed using EDXRF spectroscopy. Their differentiability was assessed by comparing each material's x-ray fluorescence spectrum and then comparing the spectra to previous research investigating differentiability in CT. To verify EDXRF's precision and accuracy, select dental specimens underwent comparative electron beam excited x-ray spectroscopy (EDS) scans, while the impact of the restorative surface area was studied by scanning a row of dental specimens with varying restorative surface areas (n = 10). EDXRF was able to differentiate all 36 possible pairs of dental filling materials; however, dual-energy CT was only able to differentiate 33 out of 36. The EDS scans showed correlating x-ray fluorescence peaks on the x-ray spectra compared to our EDXRF. In addition, the surface area showed no influence on the differentiability of the dental filling materials. EDXRF has the potential to facilitate corpse identification by differentiating and comparing restorative materials, providing more information compared to post-mortem CT alone. Despite not being able to explicitly identify a brand without a control sample or database, its fast and mobile use could accelerate daily routines or mass victim identification processes. To achieve this goal, further development of EDXRF scanners for this application and further studies evaluating the method within a specific routine need to be performed.

Simulation of mirror surfaces for virtual estimation of visibility lines for 3D motor vehicle collision reconstruction.

3D reconstructions of motor vehicle collisions are used to identify the causes of these events and to identify potential violations of traffic regulations. Thus far, the reconstruction of mirrors has been a problem since they are often based on approximations or inaccurate data. Our aim with this paper was to confirm that structured light scans of a mirror improve the accuracy of simulating the field of view of mirrors. We analyzed the performances of virtual mirror surfaces based on structured light scans using real mirror surfaces and their reflections as references. We used an ATOS GOM III scanner to scan the mirrors and processed the 3D data using Geomagic Wrap. For scene reconstruction and to generate virtual images, we used 3ds Max. We compared the simulated virtual images and photographs of real scenes using Adobe Photoshop. Our results showed that we achieved clear and even mirror results and that the mirrors behaved as expected. The greatest measured deviation between an original photo and the corresponding virtual image was 20 pixels in the transverse direction for an image width of 4256 pixels. We discussed the influences of data processing and alignment of the 3D models on the results. The study was limited to a distance of 1.6m, and the method was not able to simulate an interior mirror. In conclusion, structured light scans of mirror surfaces can be used to simulate virtual mirror surfaces with regard to 3D motor vehicle collision reconstruction.